text:
that it might emerge from a complex system; and what is a complex system, that it might give rise to a creative mind?" Complexity science is a fashionable topic these days. My perspective on complexity, however, is a somewhat unusual one: I am interested in complex systems science principally as it reflects on abstract mathematical, computational models of mind. In my three previous books, The Structure of Intelligence, Evolving Mind, and Chaotic Logic, I have outlined a comprehensive complex-systems-theoretic theory of mind that I now call the psynet model. This book is a continuation of the research program presented in my previous books (and those books will be frequently referred to here, by the nicknames EM and CL). One might summarize the trajectory of thought spanning these four books as follows. SI formulated a philosophy and mathem- ics of mind, based on theoretical computer science and the concept of "pattern. " EM analyzed the theory of evolution by natural selection in similar terms, and used this computational theory of evolution to establish the evolutionary nature of thought.},
	language = {en},
	publisher = {Springer Science \& Business Media},
	author = {Goertzel, Ben},
	month = feb,
	year = {1997},
	file = {Goertzel.1997.FromComplexityToCreativityExplorationsInEvolutionaryAutopoieticAndCognitiveDynamics.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Goertzel.1997.FromComplexityToCreativityExplorationsInEvolutionaryAutopoieticAndCognitiveDynamics.pdf:application/pdf}
}

@article{lehman_investigating_2014,
	title = {Investigating {Biological} {Assumptions} through {Radical} {Reimplementation}},
	abstract = {An important goal in both artificial life and biology is uncovering the most general principles underlying life, which might catalyze both our understanding of life and engineering life-like machines. While many such general principles have been hypothesized, conclusively testing them is difficult because life on Earth provides only a singular example from which to infer. To circumvent this limitation, this paper formalizes an approach called radical reimplementation. The idea is to investigate an abstract biological hypothesis by intentionally reimplementing its main principles to diverge maximally from existing natural examples. If the reimplementation successfully exhibits properties resembling biology it may better support the underlying hypothesis than an alternative example inspired more directly by nature. The approach thereby provides a principled alternative to a common tradition of defending and minimizing deviations from nature in artificial life. This work reviews examples that can be interpreted through the lens of radical reimplementation to yield potential insights into biology despite having purposefully unnatural experimental setups. In this way, radical reimplementation can help renew the relevance of computational systems for investigating biological theory and can act as a practical philosophical tool to help separate the fundamental features of terrestrial biology from the epiphenomenal.},
	journal = {Artificial Life},
	author = {Lehman, Joel and Stanley, Kenneth O.},
	year = {2014},
	file = {Lehman.Stanley.2014.InvestigatingBiologicalAssumptionsThroughRadicalReimplemention.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Lehman.Stanley.2014.InvestigatingBiologicalAssumptionsThroughRadicalReimplemention.pdf:application/pdf}
}

@book{schimel_writing_2012,
	title = {Writing {Science}: {How} to {Write} {Papers} {That} {Get} {Cited} and {Proposals} {That} {Get} {Funded}},
	isbn = {978-0-19-976023-7},
	shorttitle = {Writing {Science}},
	abstract = {As a scientist, you are a professional writer: your career is built on successful proposals and papers. Success isn't defined by getting papers into print, but by getting them into the reader's consciousness. Writing Science is built upon the idea that successful science writing tells a story. It uses that insight to discuss how to write more effectively. Integrating lessons from other genres of writing with those from the author's years of experience as author, reviewer, and editor, the book shows scientists and students how to present their research in a way that is clear and that will maximize reader comprehension. The book takes an integrated approach, using the principles of story structure to discuss every aspect of successful science writing, from the overall structure of a paper or proposal to individual sections, paragraphs, sentences, and words. It begins by building core arguments, analyzing why some stories are engaging and memorable while others are quickly forgotten, and proceeds to the elements of story structure, showing how the structures scientists and researchers use in papers and proposals fit into classical models. The book targets the internal structure of a paper, explaining how to write clear and professional sections, paragraphs, and sentences in a way that is clear and compelling. The ideas within a paper should flow seamlessly, drawing readers along. The final section of the book deals with special challenges, such as how to discuss research limitations and how to write for the public. Writing Science is a much-needed guide to succeeding in modern science. Its insights and strategies will equip science students, scientists, and professionals across a wide range of scientific and technical fields with the tools needed to communicate effectively.},
	language = {en},
	publisher = {Oxford University Press},
	author = {Schimel, Joshua},
	year = {2012},
	file = {Schimel.2012WritingScienceHowtoWritePapers.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Schimel.2012WritingScienceHowtoWritePapers.pdf:application/pdf}
}

@unpublished{napp_message_2013,
	address = {Cambridge},
	title = {Message {Passing} {Inference} with {Chemical} {Reaction} {Networks}},
	abstract = {Recent work on molecular programming has explored new possibilities for computational
abstractions with biomolecules, including logic gates, neural networks,
and linear systems. In the future such abstractions might enable nanoscale devices
that can sense and control the world at a molecular scale. Just as in macroscale
robotics, it is critical that such devices can learn about their environment and reason
under uncertainty. At this small scale, systems are typically modeled as chemical
reaction networks. In this work, we develop a procedure that can take arbitrary
probabilistic graphical models, represented as factor graphs over discrete random
variables, and compile theminto chemical reaction networks that implement inference.
In particular, we show that marginalization based on sum-product message
passing can be implemented in terms of reactions between chemical species whose
concentrations represent probabilities. We show algebraically that the steady state
concentration of these species correspond to the marginal distributions of the random
variables in the graph and validate the results in simulations. As with standard
sum-product inference, this procedure yields exact results for tree-structured
graphs, and approximate solutions for loopy graphs},
	author = {Napp, Nils and Adams, Ryan Prescott},
	year = {2013},
	file = {Napp.Adams.2013.MessagePassingInferenceWithChemicalReactionNetworks.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Napp.Adams.2013.MessagePassingInferenceWithChemicalReactionNetworks.pdf:application/pdf}
}

@book{weiss_multiagent_1999,
	title = {Multiagent {Systems}: {A} {Modern} {Approach} to {Distributed} {Artificial} {Intelligence}},
	isbn = {978-0-262-73131-7},
	shorttitle = {Multiagent {Systems}},
	abstract = {This is the first comprehensive introduction to multiagent systems and contemporarydistributed artificial intelligence that is suitable as a textbook. The book provides detailedcoverage of basic topics as well as several closely related ones.Unliketraditional textbooks, the book brings together many leading experts, guaranteeing a broad anddiverse base of knowledge and expertise. It emphasizes aspects of both theory and application, andprovides many illustrations and examples. Also included are thought-provoking exercises of varyingdegrees of difficulty and a twenty-page glossary of terms found in the study of agents, multiagentsystems, and distributed artificial intelligence.The book can be used forteaching as well as self-study, and is designed to meet the needs of both researchers andpractitioners. In view of the interdisciplinary nature of the field, it will be a useful referencenot only for computer scientists and engineers, but for social scientists and management andorganization scientists as well.Contributors: Gul A. Agha, Kathleen M. Carley,Jose Cuena, Edmund H. Durfee, Clarence Ellis, Les Gasser, Michael P. Georgeff, Michael N. Huhns,Toru Ishida, Nadeem Jamali, Sascha Ossowski, H. Van Dyke Parunak, Anand S. Rao, Tuomas W. Sandholm,Sandip Sen, Munindar P. Singh, Larry M. Stephens, Gerard Tel, Jacques Wainer, Gerhard Weiss, MichaelJ. Wooldridge, Makoto Yokoo.},
	language = {en},
	publisher = {MIT Press},
	author = {Weiss, Gerhard},
	year = {1999},
	keywords = {vveitas:distributed\_systems},
	file = {Weiss.1999.MultiagentSystemsAModernpproachToArtificialIntelligence.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Weiss.1999.MultiagentSystemsAModernpproachToArtificialIntelligence.pdf:application/pdf}
}

@article{de_jaegher_participatory_2007,
	title = {Participatory sense-making},
	volume = {6},
	url = {http://lifecognitionschool.ias-research.net/files/2010/06/dejaegherdipaolo07participatorysensemaking.pdf},
	number = {4},
	journal = {Phenomenology and the cognitive sciences},
	author = {De Jaegher, Hanne and Di Paolo, Ezequiel},
	year = {2007},
	keywords = {vveitas:cognitive\_development},
	pages = {485--507},
	file = {Jaegher.DiPaolo.ParticipatorySenseMaking.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Jaegher.DiPaolo.ParticipatorySenseMaking.pdf:application/pdf}
}

@misc{mcgann_enactive_2008,
	title = {Enactive {Cognition}: {A} {Cognition} {Briefing}},
	url = {http://www.vernon.eu/euCognition/cognition_briefing_enactive_cognition.htm},
	language = {English},
	urldate = {2014-09-23},
	author = {McGann, Marek},
	year = {2008},
	keywords = {vveitas:cognitive\_development},
	file = {McGann.EnactiveCognition.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/McGann.EnactiveCognition.pdf:application/pdf}
}

@book{eliasmith_how_2013,
	address = {Oxford},
	edition = {1 edition},
	title = {How to {Build} a {Brain}: {A} {Neural} {Architecture} for {Biological} {Cognition}},
	isbn = {978-0-19-979454-6},
	shorttitle = {How to {Build} a {Brain}},
	abstract = {One goal of researchers in neuroscience, psychology, and artificial intelligence is to build theoretical models that are able to explain the flexibility and adaptiveness of biological systems. How to build a brain provides a detailed guided exploration of a new cognitive architecture that takes biological detail seriously, while addressing cognitive phenomena.  The Semantic Pointer Architecture (SPA) introduced in this book provides a set of tools for constructing a wide range of biologically constrained perceptual, cognitive, and motor models. Examples of such models are provided, and they are shown to explain a wide range of data including single cell recordings, neural population activity, reaction times, error rates, choice behavior, and fMRI signals. Each of these models introduces a major feature of biological cognition addressed in the book, including semantics, syntax, control, learning, and memory. These models are not introduced as independent considerations of brain function, but instead integrated to give rise to what is currently the world's largest functional brain model. The last half of this book compares the Semantic Pointer Architecture with the current state-of-the-art, addressing issues of theory construction in the behavioral sciences, semantic compositionality, and scalability, among other considerations. The book concludes with a discussion of conceptual challenges raised by this architecture, and identifies several outstanding challenges for this, and other, cognitive architectures. Along the way, the book considers neural coding, concept representation, neural dynamics, working memory, neuroanatomy, reinforcement learning, and spike-timing dependent plasticity. The book includes 8 detailed, hands-on tutorials exploiting the free Nengo neural simulation environment, providing practical experience with the concepts and models presented throughout.},
	language = {English},
	publisher = {Oxford University Press},
	author = {Eliasmith, Chris},
	month = jun,
	year = {2013},
	file = {Eliasmith.2013.HowToBuildABrainANeuralArchitectureForBiologicalCognition.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Eliasmith.2013.HowToBuildABrainANeuralArchitectureForBiologicalCognition.pdf:application/pdf}
}

@inproceedings{rohde_multisensory_2010,
	title = {Multisensory {Perceptual} {Discrimination} in {Evolved} {Networks} and {Agents}.},
	booktitle = {{ALIFE}},
	author = {Rohde, Marieke},
	year = {2010},
	keywords = {vveitas:generative\_model},
	pages = {607--614},
	file = {Rohde.2010.MultisensoryPerceptualDisctiminationInEvolvedNetworksAndAgents.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rohde.2010.MultisensoryPerceptualDisctiminationInEvolvedNetworksAndAgents.pdf:application/pdf}
}

@article{di_paolo_homeostatic_2000,
	title = {Homeostatic adaptation to inversion of the visual field and other sensorimotor disruptions},
	volume = {6},
	journal = {From animals to animats},
	author = {Di Paolo, Ezequiel A},
	year = {2000},
	keywords = {vveitas:generative\_model},
	pages = {440--449},
	file = {DiPaolo.2000.HomeostaticAdaptationToInversionOfTheVisualField.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/DiPaolo.2000.HomeostaticAdaptationToInversionOfTheVisualField.pdf:application/pdf}
}

@article{harvey_evolutionary_2005,
	title = {Evolutionary {Robotics}: {A} {New} {Scientific} {Tool} for {Studying} {Cognition}},
	volume = {11},
	issn = {1064-5462},
	shorttitle = {Evolutionary {Robotics}},
	url = {http://dx.doi.org/10.1162/1064546053278991},
	doi = {10.1162/1064546053278991},
	abstract = {We survey developments in artificial neural networks, in behavior-based robotics, and in evolutionary algorithms that set the stage for evolutionary robotics (ER) in the 1990s. We examine the motivations for using ER as a scientific tool for studying minimal models of cognition, with the advantage of being capable of generating integrated sensorimotor systems with minimal (or controllable) prejudices. These systems must act as a whole in close coupling with their environments, which is an essential aspect of real cognition that is often either bypassed or modeled poorly in other disciplines. We demonstrate with three example studies: homeostasis under visual inversion, the origins of learning, and the ontogenetic acquisition of entrainment.},
	number = {1-2},
	urldate = {2014-12-08},
	journal = {Artificial Life},
	author = {Harvey, Inman and Paolo, Ezequiel Di and Wood, Rachel and Quinn, Matt and Tuci, Elio},
	month = jan,
	year = {2005},
	pages = {79--98},
	file = {Harvey.EtAl.2005.EvolutionaryRoboticsANewScientificToolForStudyingCognition.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Harvey.EtAl.2005.EvolutionaryRoboticsANewScientificToolForStudyingCognition.pdf:application/pdf}
}

@article{seth_measuring_2008,
	title = {Measuring consciousness: relating behavioural and neurophysiological approaches},
	volume = {12},
	number = {8},
	journal = {Trends in cognitive sciences},
	author = {Seth, Anil K and Dienes, Zoltán and Cleeremans, Axel and Overgaard, Morten and Pessoa, Luiz},
	year = {2008},
	pages = {314--321},
	file = {Seth.EtAl.2008.MeasuringConsciousnessRelatingBehavioralAndNeurophisiologicalApproaches.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Seth.EtAl.2008.MeasuringConsciousnessRelatingBehavioralAndNeurophisiologicalApproaches.pdf:application/pdf}
}

@article{goertzel_characterizing_nodate,
	title = {Characterizing {Human}-{Like} {Consciousness}: {An} {Integrative} {Approach}},
	abstract = {Synthesizing concepts and findings from a number of recent models of
human consciousness, a unified model of the key properties characteriz-
ing human consciousness is outlined. Six key properties are emphasized:
Dynamical representation of the focus of consciousness, Focusing of
energetic resources and focusing of informational resources on a
subset of system knowledge, Global Workspace dynamics as outlined
by Bernard Baars in his cognitive theory of consciousness, Integrated In-
formation as emphasized by Tononi, and correlation of attentional
focus with self-modeling. It is proposed that the extent, and relative
importance, of these properties may vary in different states of conscious-
ness; and that any AI system displaying closely human-like intelligence
will need to manifest these properties in its consciousness as well. The
“hard problem” of consciousness is sidestepped throughout, via focusing
on structures and dynamics posited to serve as neural or cognitive corre-
lates of subjective conscious experience.},
	author = {Goertzel, Ben},
	keywords = {vveitas:generative\_model},
	file = {Goertzel.2014.CharacterizingHumanLIkeConsciounseeAnIntegrativeApproach.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Goertzel.2014.CharacterizingHumanLIkeConsciounseeAnIntegrativeApproach.pdf:application/pdf}
}

@misc{rodriguez_understanding_nodate,
	title = {Understanding the {World} using {Tables} and {Graphs}},
	url = {http://thinkaurelius.com/2012/03/22/understanding-the-world-using-tables-and-graphs/},
	abstract = {Organizations make use of data to drive their decision making, enhance their product features, and to increase the efficiency of their everyday operations. Data by itself is not useful. However, wi...},
	urldate = {2014-08-18},
	journal = {Aurelius},
	author = {Rodriguez, Marko},
	file = {Rodriguez.2012.UnderstandingTheWorldUsingTablesAndGraphs.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2012.UnderstandingTheWorldUsingTablesAndGraphs.pdf:application/pdf}
}

@misc{rodriguez_structural_nodate,
	title = {Structural {Abstractions} in {Brains} and {Graphs}},
	url = {http://thinkaurelius.com/2012/05/08/structural-abstractions-in-brains-and-graphs/},
	abstract = {A graph database is a software system that persists and represents data as a collection of vertices (i.e. nodes, dots) connected to one another by a collection of edges (i.e. links, lines). These d...},
	urldate = {2014-08-18},
	journal = {Aurelius},
	author = {Rodriguez, Marko},
	file = {Rodriguez.2012.StructuralAabstracionsInBrainsAndGraphs.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2012.StructuralAabstracionsInBrainsAndGraphs.pdf:application/pdf}
}

@misc{rodriguez_graph_nodate-1,
	title = {Graph {Degree} {Distributions} using {R} over {Hadoop}},
	url = {http://www.javacodegeeks.com/2014/06/graph-degree-distributions-using-r-over-hadoop.html},
	abstract = {There are two common types of graph engines. One type is focused on providing real-time, traversal-based algorithms over linked-list graphs represented on a single-server. Such engines are typically called graph databases and some of the vendors include Neo4j, OrientDB, DEX, and InfiniteGraph. The other type of graph engine is focused on batch-processing using vertex-centric message passing within a graph represented across a cluster of machines. Graph engines of this form include Hama, Golden Orb, Giraph, and Pregel. The purpose of this post is to demonstrate how to express the computation of two fundamental graph statistics — each as a graph traversal and as a MapReduce algorithm. The graph engines explored for this purpose are Neo4j and Hadoop. However, with respects to Hadoop, instead of focusing on a particular vertex-centric BSP-based graph-processing package such as Hama or Giraph, the results presented are via native Hadoop (HDFS + MapReduce). Moreover, instead of developing},
	urldate = {2014-08-18},
	journal = {Java Code Geeks},
	author = {Rodriguez, Marko},
	file = {Rodriguez.2012.GraphDegreeDistributionsUsingROverHadoop.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2012.GraphDegreeDistributionsUsingROverHadoop.pdf:application/pdf}
}

@misc{rodriguez_local_nodate,
	title = {Local and {Distributed} {Traversal} {Engines}},
	url = {http://markorodriguez.com/2011/04/19/local-and-distributed-traversal-engines/},
	abstract = {In the graph database space, there are two types of traversal engines: local and distributed. Local traversal engines are typically for single-machine graph databases and are used for real-time pro...},
	urldate = {2014-08-18},
	journal = {Marko A. Rodriguez},
	author = {Rodriguez, Marko},
	file = {Rodriguez.2011.LocalAndDistributedTraversalEngines.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2011.LocalAndDistributedTraversalEngines.pdf:application/pdf}
}

@misc{marko_rodriguez_problem-solving_nodate,
	type = {Technology},
	title = {Problem-{Solving} using {Graph} {Traversals}: {Searching}, {Scoring}, {Ranking}, …},
	copyright = {© All Rights Reserved},
	shorttitle = {Problem-{Solving} using {Graph} {Traversals}},
	url = {http://www.slideshare.net/slidarko/problemsolving-using-graph-traversals-searching-scoring-ranking-and-recommendation},
	abstract = {A graph is a data structure that links a set of vertices by a set of edges. Modern graph databases support multi-relational graph structures, where there exist different types of vertices (e.g. people, places, items) and different types of edges (e.g. friend, lives at, purchased). By means of index-free adjacency, graph databases are optimized for graph traversals and are interacted with through a graph traversal engine. A graph traversal is defined as an abstract path whose instance is realized on a graph dataset. Graph databases and traversals can be used for searching, scoring, ranking, and in concert, recommendation. This presentation will explore graph structures, algorithms, traversal algebras, graph-related software suites, and a host of examples demonstrating how to solve real-world problems, in real-time, with graphs. This is a whirlwind tour of the theory and application of graphs.},
	urldate = {2014-08-18},
	author = {Marko Rodriguez},
	file = {Rodriguez.2010.Problem-SolvingUsingGraphTraversals.Presentation.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2010.Problem-SolvingUsingGraphTraversals.Presentation.pdf:application/pdf}
}

@article{rodriguez_constructions_2010,
	title = {Constructions from {Dots} and {Lines}},
	url = {http://arxiv.org/abs/1006.2361},
	abstract = {A graph is a data structure composed of dots (i.e. vertices) and lines (i.e. edges). The dots and lines of a graph can be organized into intricate arrangements. The ability for a graph to denote objects and their relationships to one another allow for a surprisingly large number of things to be modeled as a graph. From the dependencies that link software packages to the wood beams that provide the framing to a house, most anything has a corresponding graph representation. However, just because it is possible to represent something as a graph does not necessarily mean that its graph representation will be useful. If a modeler can leverage the plethora of tools and algorithms that store and process graphs, then such a mapping is worthwhile. This article explores the world of graphs in computing and exposes situations in which graphical models are beneficial.},
	urldate = {2014-08-18},
	journal = {arXiv:1006.2361 [cs]},
	author = {Rodriguez, Marko A. and Neubauer, Peter},
	month = jun,
	year = {2010},
	note = {arXiv: 1006.2361},
	file = {Rodriguez.2010.ConstructionsFromDotsAndLines.PDF:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2010.ConstructionsFromDotsAndLines.PDF:application/pdf}
}

@article{rodriguez_faith_2009,
	title = {Faith in the {Algorithm}, {Part} 1: {Beyond} the {Turing} {Test}},
	shorttitle = {Faith in the {Algorithm}, {Part} 1},
	url = {http://arxiv.org/abs/0903.0200},
	abstract = {Since the Turing test was first proposed by Alan Turing in 1950, the primary goal of artificial intelligence has been predicated on the ability for computers to imitate human behavior. However, the majority of uses for the computer can be said to fall outside the domain of human abilities and it is exactly outside of this domain where computers have demonstrated their greatest contribution to intelligence. Another goal for artificial intelligence is one that is not predicated on human mimicry, but instead, on human amplification. This article surveys various systems that contribute to the advancement of human and social intelligence.},
	urldate = {2014-08-18},
	journal = {arXiv:0903.0200 [cs]},
	author = {Rodriguez, Marko A. and Pepe, Alberto},
	month = mar,
	year = {2009},
	note = {arXiv: 0903.0200},
	file = {Rodriguez.Pepe.2009.FaithInTheAlgorithm1BeyondTheTuringTest.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.Pepe.2009.FaithInTheAlgorithm1BeyondTheTuringTest.pdf:application/pdf}
}

@article{rodriguez_faith_2009-1,
	title = {Faith in the {Algorithm}, {Part} 2: {Computational} {Eudaemonics}},
	shorttitle = {Faith in the {Algorithm}, {Part} 2},
	url = {http://arxiv.org/abs/0904.0027},
	abstract = {Eudaemonics is the study of the nature, causes, and conditions of human well-being. According to the ethical theory of eudaemonia, reaping satisfaction and fulfillment from life is not only a desirable end, but a moral responsibility. However, in modern society, many individuals struggle to meet this responsibility. Computational mechanisms could better enable individuals to achieve eudaemonia by yielding practical real-world systems that embody algorithms that promote human flourishing. This article presents eudaemonic systems as the evolutionary goal of the present day recommender system.},
	urldate = {2014-08-18},
	journal = {arXiv:0904.0027 [cs]},
	author = {Rodriguez, Marko A. and Watkins, Jennifer H.},
	month = apr,
	year = {2009},
	note = {arXiv: 0904.0027}
}

@article{rodriguez_exposing_2010,
	title = {Exposing {Multi}-{Relational} {Networks} to {Single}-{Relational} {Network} {Analysis} {Algorithms}},
	volume = {4},
	issn = {17511577},
	url = {http://arxiv.org/abs/0806.2274},
	doi = {10.1016/j.joi.2009.06.004},
	abstract = {Many, if not most network analysis algorithms have been designed specifically for single-relational networks; that is, networks in which all edges are of the same type. For example, edges may either represent "friendship," "kinship," or "collaboration," but not all of them together. In contrast, a multi-relational network is a network with a heterogeneous set of edge labels which can represent relationships of various types in a single data structure. While multi-relational networks are more expressive in terms of the variety of relationships they can capture, there is a need for a general framework for transferring the many single-relational network analysis algorithms to the multi-relational domain. It is not sufficient to execute a single-relational network analysis algorithm on a multi-relational network by simply ignoring edge labels. This article presents an algebra for mapping multi-relational networks to single-relational networks, thereby exposing them to single-relational network analysis algorithms.},
	number = {1},
	urldate = {2014-08-18},
	journal = {Journal of Informetrics},
	author = {Rodriguez, Marko A. and Shinavier, Joshua},
	month = jan,
	year = {2010},
	note = {arXiv: 0806.2274},
	pages = {29--41},
	file = {Rodriguez.2009.ExposingMultiRelationalNeowrksToSingleRelationalNetowrkAnalysisAlgorithms.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2009.ExposingMultiRelationalNeowrksToSingleRelationalNetowrkAnalysisAlgorithms.pdf:application/pdf}
}

@article{rodriguez_automatic_2009,
	title = {Automatic {Metadata} {Generation} using {Associative} {Networks}},
	volume = {27},
	issn = {10468188},
	url = {http://arxiv.org/abs/0807.0023},
	doi = {10.1145/1462198.1462199},
	abstract = {In spite of its tremendous value, metadata is generally sparse and incomplete, thereby hampering the effectiveness of digital information services. Many of the existing mechanisms for the automated creation of metadata rely primarily on content analysis which can be costly and inefficient. The automatic metadata generation system proposed in this article leverages resource relationships generated from existing metadata as a medium for propagation from metadata-rich to metadata-poor resources. Because of its independence from content analysis, it can be applied to a wide variety of resource media types and is shown to be computationally inexpensive. The proposed method operates through two distinct phases. Occurrence and co-occurrence algorithms first generate an associative network of repository resources leveraging existing repository metadata. Second, using the associative network as a substrate, metadata associated with metadata-rich resources is propagated to metadata-poor resources by means of a discrete-form spreading activation algorithm. This article discusses the general framework for building associative networks, an algorithm for disseminating metadata through such networks, and the results of an experiment and validation of the proposed method using a standard bibliographic dataset.},
	number = {2},
	urldate = {2014-08-17},
	journal = {ACM Transactions on Information Systems},
	author = {Rodriguez, Marko A. and Bollen, Johan and Van de Sompel, Herbert},
	month = feb,
	year = {2009},
	note = {arXiv: 0807.0023},
	pages = {1--20},
	file = {Rodriguez.2009.AutomaticMetadataGenerationUsingAssociativeNetworks.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2009.AutomaticMetadataGenerationUsingAssociativeNetworks.pdf:application/pdf}
}

@article{rodriguez_mapping_2008,
	title = {Mapping {Semantic} {Networks} to {Undirected} {Networks}},
	url = {http://arxiv.org/abs/0804.0277},
	abstract = {There exists an injective, information-preserving function that maps a semantic network (i.e a directed labeled network) to a directed network (i.e. a directed unlabeled network). The edge label in the semantic network is represented as a topological feature of the directed network. Also, there exists an injective function that maps a directed network to an undirected network (i.e. an undirected unlabeled network). The edge directionality in the directed network is represented as a topological feature of the undirected network. Through function composition, there exists an injective function that maps a semantic network to an undirected network. Thus, aside from space constraints, the semantic network construct does not have any modeling functionality that is not possible with either a directed or undirected network representation. Two proofs of this idea will be presented. The first is a proof of the aforementioned function composition concept. The second is a simpler proof involving an undirected binary encoding of a semantic network.},
	urldate = {2014-08-17},
	journal = {arXiv:0804.0277 [cs]},
	author = {Rodriguez, Marko A.},
	month = apr,
	year = {2008},
	note = {arXiv: 0804.0277},
	file = {Rodriguez.2008.MappingSemanticNetworksToUndirectedNetworks.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2008.MappingSemanticNetworksToUndirectedNetworks.pdf:application/pdf}
}

@article{rodriguez_grammar-based_2008,
	title = {Grammar-based random walkers in semantic networks},
	volume = {21},
	issn = {0950-7051},
	url = {http://www.sciencedirect.com/science/article/pii/S0950705108000798},
	doi = {10.1016/j.knosys.2008.03.030},
	abstract = {Semantic networks qualify the meaning of an edge relating any two vertices. Determining which vertices are most “central” in a semantic network is difficult because one relationship type may be deemed subjectively more important than another. For this reason, research into semantic network metrics has focused primarily on context-based rankings (i.e. user prescribed contexts). Moreover, many of the current semantic network metrics rank semantic associations (i.e. directed paths between two vertices) and not the vertices themselves. This article presents a framework for calculating semantically meaningful primary eigenvector-based metrics such as eigenvector centrality and PageRank in semantic networks using a modified version of the random walker model of Markov chain analysis. Random walkers, in the context of this article, are constrained by a grammar, where the grammar is a user-defined data structure that determines the meaning of the final vertex ranking. The ideas in this article are presented within the context of the Resource Description Framework (RDF) of the Semantic Web initiative.},
	number = {7},
	urldate = {2014-08-17},
	journal = {Knowledge-Based Systems},
	author = {Rodriguez, Marko A.},
	month = oct,
	year = {2008},
	keywords = {vveitas:graphical\_models},
	pages = {727--739}
}

@inproceedings{rodriguez_social_2007,
	title = {Social {Decision} {Making} with {Multi}-{Relational} {Networks} and {Grammar}-{Based} {Particle} {Swarms}},
	doi = {10.1109/HICSS.2007.487},
	abstract = {Social decision support systems are able to aggregate the local perspectives of a diverse group of individuals into a global social decision. This paper presents a multi-relational network ontology and grammar-based particle swarm algorithm capable of aggregating the decisions of millions of individuals. This framework supports a diverse problem space and a broad range of vote aggregation algorithms. These algorithms account for individual expertise and representation across different domains of the group problem space. Individuals are able to pose and categorize problems, generate potential solutions, choose trusted representatives, and vote for particular solutions. Ultimately, via a social decision making algorithm, the system aggregates all the individual votes into a single collective decision},
	booktitle = {40th {Annual} {Hawaii} {International} {Conference} on {System} {Sciences}, 2007. {HICSS} 2007},
	author = {Rodriguez, M.A},
	month = jan,
	year = {2007},
	pages = {39--39},
	file = {Rodriguez.2007.SocialDecisionMakingWithMulti-RelationalNetworksAndGrammerBasedParticleSwarms.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2007.SocialDecisionMakingWithMulti-RelationalNetworksAndGrammerBasedParticleSwarms.pdf:application/pdf}
}

@article{rodriguez_modeling_2007,
	title = {Modeling {Computations} in a {Semantic} {Network}},
	url = {http://arxiv.org/abs/0706.0022},
	abstract = {Semantic network research has seen a resurgence from its early history in the cognitive sciences with the inception of the Semantic Web initiative. The Semantic Web effort has brought forth an array of technologies that support the encoding, storage, and querying of the semantic network data structure at the world stage. Currently, the popular conception of the Semantic Web is that of a data modeling medium where real and conceptual entities are related in semantically meaningful ways. However, new models have emerged that explicitly encode procedural information within the semantic network substrate. With these new technologies, the Semantic Web has evolved from a data modeling medium to a computational medium. This article provides a classification of existing computational modeling efforts and the requirements of supporting technologies that will aid in the further growth of this burgeoning domain.},
	urldate = {2014-08-17},
	journal = {arXiv:0706.0022 [cs]},
	author = {Rodriguez, Marko A. and Bollen, Johan},
	month = may,
	year = {2007},
	note = {arXiv: 0706.0022},
	file = {Rodriguez.2007.ModelingComputationsInASemanticNetwork.PDF:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2007.ModelingComputationsInASemanticNetwork.PDF:application/pdf}
}

@misc{rodriguez_boutique_nodate,
	title = {Boutique {Graph} {Data} with {Titan}},
	url = {http://thinkaurelius.com/2013/11/24/boutique-graph-data-with-titan/},
	abstract = {Titan is a distributed graph database capable of supporting graphs on the order of 100 billion edges and sustaining on the order of 1 billion transactions a day (see Educating the Planet with Pears...},
	urldate = {2014-08-17},
	journal = {Aurelius},
	author = {Rodriguez, Marko},
	file = {Rodriguez.2013.BoutiqueGraphDataWithTitan.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2013.BoutiqueGraphDataWithTitan.pdf:application/pdf}
}

@misc{rodriguez_graphs_2011,
	title = {Graphs, {Brains}, and {Gremlin}},
	url = {http://markorodriguez.com/2011/07/14/graphs-brains-and-gremlin/},
	abstract = {What do graphs and brains have in common? First, they both share a relatively similar structure: Vertices/neurons are connected to each other by edges/axons. Second, they both share a similar proce...},
	urldate = {2014-08-17},
	journal = {Marko A. Rodriguez},
	author = {Rodriguez, Marko},
	year = {2011},
	file = {Rodriguez.2011.GraphsBrainsAndGremlin.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2011.GraphsBrainsAndGremlin.pdf:application/pdf}
}

@article{rodriguez_dilated_2010,
	title = {The {Dilated} {Triple}},
	url = {http://arxiv.org/abs/1006.1080},
	abstract = {The basic unit of meaning on the Semantic Web is the RDF statement, or triple, which combines a distinct subject, predicate and object to make a definite assertion about the world. A set of triples constitutes a graph, to which they give a collective meaning. It is upon this simple foundation that the rich, complex knowledge structures of the Semantic Web are built. Yet the very expressiveness of RDF, by inviting comparison with real-world knowledge, highlights a fundamental shortcoming, in that RDF is limited to statements of absolute fact, independent of the context in which a statement is asserted. This is in stark contrast with the thoroughly context-sensitive nature of human thought. The model presented here provides a particularly simple means of contextualizing an RDF triple by associating it with related statements in the same graph. This approach, in combination with a notion of graph similarity, is sufficient to select only those statements from an RDF graph which are subjectively most relevant to the context of the requesting process.},
	urldate = {2014-08-17},
	journal = {arXiv:1006.1080 [cs]},
	author = {Rodriguez, Marko A. and Pepe, Alberto and Shinavier, Joshua},
	month = jun,
	year = {2010},
	note = {arXiv: 1006.1080},
	file = {Rodriguez.2010.TheDillatedTripple.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2010.TheDillatedTripple.pdf:application/pdf}
}

@misc{rodriguez_loopy_nodate,
	title = {Loopy {Lattices}},
	url = {http://thinkaurelius.com/2012/04/21/loopy-lattices/},
	abstract = {A lattice is a graph that has a particular, well-defined structure. An nxn lattice is a 2-dimensional grid where there are n edges along its x-axis and n edges along its y-axis. An example 20x20 la...},
	urldate = {2014-08-17},
	journal = {Aurelius},
	author = {Rodriguez, Marko},
	file = {Rodriguez.2012.LoopyLattices.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rodriguez.2012.LoopyLattices.pdf:application/pdf}
}

@book{rescher_process_2000,
	address = {Pittsburgh},
	edition = {1 edition},
	title = {Process {Philosophy}: {A} {Survey} of {Basic} {Issues}},
	isbn = {978-0-8229-6128-4},
	shorttitle = {Process {Philosophy}},
	abstract = {Process Philosophy surveys the basic issues and controversies surrounding the philosophical approach known as “process philosophy.” Process philosophy views temporality, activity, and change as the cardinal factors for our understanding of the real—process has priority over product, both ontologically and epistemically. Rescher examines the movement’s historical origins, reflecting a major line of thought in the work of such philosophers as Heracleitus, Leibniz, Bergson, Peirce, William James, and especially A. N. Whitehead.},
	language = {English},
	publisher = {University of Pittsburgh Press},
	author = {Rescher, Nicholas},
	month = dec,
	year = {2000},
	keywords = {vveitas:philosophy},
	file = {Rescher.2000ProcessPhilosophyASurveyOfBasicIssues.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rescher.2000ProcessPhilosophyASurveyOfBasicIssues.pdf:application/pdf}
}

@article{rasmussen_note_1997,
	title = {A note on simulation and dynamical hierarchies},
	journal = {Self Organization in Complex Structures-From Individual to Collective Dynamics},
	author = {Rasmussen, C Barrett S and Baas, N and Olesen, M},
	year = {1997},
	pages = {83--90},
	file = {Rasmusen.1996.ANoteOnSimulationAndDynamicalHierarchies.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Rasmusen.1996.ANoteOnSimulationAndDynamicalHierarchies.pdf:application/pdf}
}

@inproceedings{mayer_self-reproduction_1998,
	title = {Self-reproduction of dynamical hierarchies in chemical systems},
	booktitle = {Artificial life {VI}},
	author = {Mayer, Bernd and Rasmussen, Steen},
	year = {1998},
	pages = {123--129},
	file = {Mayer.Rassmusen.1998.SelfReproductionOfDynamicalHierarchiesInChemicalSystems.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Mayer.Rassmusen.1998.SelfReproductionOfDynamicalHierarchiesInChemicalSystems.pdf:application/pdf}
}

@phdthesis{potter_design_1997,
	address = {Fairfax, Virginia},
	type = {{PhD} {Thesis}},
	title = {The {Design} and {Analysis} of a {Computational} {Model} of {Cooperative} {Coevolution}},
	abstract = {As evolutionary algorithms are applied to the solution of increasingly complex systems,
explicit notions of modularity must be introduced to provide reasonable opportunities for
solutions to evolve in the form of interacting coadapted subcomponents. The di culty
comes in nding computational extensions to our current evolutionary paradigms in which
such subcomponents {\textbackslash}emerge" rather than being hand designed. At issue is how to identify
and represent such subcomponents, provide an environment in which they can interact
and coadapt, and apportion credit to them for their contributions to the problem-solving
activity such that their evolution proceeds without human involvement},
	school = {George Mason University},
	author = {Potter, Michael},
	year = {1997},
	keywords = {vveitas:distributed\_systems},
	file = {Potter.1997.TheDesignAndAnalysisOfAComputationalModelOfCooperativeCoevolutionPhDThesis.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Potter.1997.TheDesignAndAnalysisOfAComputationalModelOfCooperativeCoevolutionPhDThesis.pdf:application/pdf}
}

@article{yukalov_self-organization_2014,
	title = {Self-organization in complex systems as decision making},
	url = {http://arxiv.org/abs/1408.1529},
	abstract = {The idea is advanced that self-organization in complex systems can be treated as decision making (as it is performed by humans) and, vice versa, decision making is nothing but a kind of self-organization in the decision maker nervous systems. A mathematical formulation is suggested based on the definition of probabilities of system states, whose particular cases characterize the probabilities of structures, patterns, scenarios, or prospects. In this general framework, it is shown that the mathematical structures of self-organization and of decision making are identical. This makes it clear how self-organization can be seen as an endogenous decision making process and, reciprocally, decision making occurs via an endogenous self-organization. The approach is illustrated by phase transitions in large statistical systems, crossovers in small statistical systems, evolutions and revolutions in social and biological systems, structural self-organization in dynamical systems, and by the probabilistic formulation of classical and behavioral decision theories. In all these cases, self-organization is described as the process of evaluating the probabilities of macroscopic states or prospects in the search for a state with the largest probability. The general way of deriving the probability measure for classical systems is the principle of minimal information, that is, the conditional entropy maximization under given constraints. Behavioral biases of decision makers can be characterized in the same way as analogous to quantum fluctuations in natural systems.},
	urldate = {2014-08-17},
	journal = {arXiv:1408.1529 [nlin, physics:physics]},
	author = {Yukalov, V. I. and Sornette, D.},
	month = aug,
	year = {2014},
	note = {arXiv: 1408.1529},
	file = {Yukalov.Sornette.2014.SelfOrganizationInComplexSystemsAsDecisionMaking.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Yukalov.Sornette.2014.SelfOrganizationInComplexSystemsAsDecisionMaking.pdf:application/pdf}
}

@techreport{peng_experimentation_2005,
	address = {Singapore},
	type = {Honours {Year} {Project} {Report}},
	title = {An {Experimentation} {Platform} for {Graph} {Chemistries}},
	url = {http://prl.lib.hku.hk/exhibits/show/prdla/detail-record?itemid=304468},
	abstract = {In the area of Artificial Life, many Artificial Chemistries that are used to understand the
properties of life have not been very convincing so far. This project proposes a new Artificial
Chemistry Design working on graph-based molecules. Graphs interact with each other using a
generic formalism. A platform is implemented to support experimentation and analysis in
such chemistry. Through current and future experiments, the tool aims to facilitate
understanding of behavioral and conditional aspects of life. A notion of Self-Replication
which is rarely studied in other graph-based chemistries is formalized. Case studies are
presented as a demonstration of the capabilities of the platform. One of the case studies hinted
on the possibility that homeostasis has taken place.},
	number = {Project No: H041090},
	institution = {National University of Singapore},
	author = {Peng, Cua Bee},
	year = {2005},
	pages = {56},
	file = {Peng.2005.AnExperimentationPlatformForGraphChemistries.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Peng.2005.AnExperimentationPlatformForGraphChemistries.pdf:application/pdf}
}

@book{bruner_making_2003,
	title = {Making {Stories}: {Law}, {Literature}, {Life}},
	isbn = {978-0-674-01099-4},
	shorttitle = {Making {Stories}},
	abstract = {Stories pervade our daily lives, from human interest news items, to a business strategy described to a colleague, to daydreams between chores. Stories are what we use to make sense of the world. But how does this work? In Making Stories, the eminent psychologist Jerome Bruner examines this pervasive human habit and suggests new and deeper ways to think about how we use stories to make sense of lives and the great moral and psychological problems that animate them. Looking at legal cases and autobiography as well as literature, Bruner warns us not to be seduced by overly tidy stories and shows how doubt and double meaning can lie beneath the most seemingly simple case.},
	language = {en},
	publisher = {Harvard University Press},
	author = {Bruner, Jerome Seymour},
	year = {2003},
	file = {Bruner.2003.MakingStories.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Bruner.2003.MakingStories.pdf:application/pdf}
}

@book{summers_object_1994,
	title = {Object {Relations} {Theories} and {Psychopathology}: {A} {Comprehensive} {Text}},
	isbn = {978-0-88163-155-5},
	shorttitle = {Object {Relations} {Theories} and {Psychopathology}},
	abstract = {Object relations theories, both British and American, have achieved increasing prominence in recent years as the limitations of the classical psychoanalytic model have become more apparent. Despite the plethora of books written from an object relations perspective, there has to date been no textbook describing and comparing the various theories with a focus on their clinical applications. Object Relations Theories and Psychopathology: A Comprehensive Text brilliantly fills this gap in the literature.Frank Summers provides thorough, lucid, and critically informed accounts of the work of each of the major object relations theorists: Fairbairn, Guntrip, Melanie Klein, Winnicott, Kernberg, and Kohut. His expositions achieve distinction on two counts. First, the work of each object relations theorist is presented as a comprehensive whole, with separate sections of each chapter expounding the theorist's ideas and assumptions about metapsychology, development, psychopathology, and treatment. Summers concludes each account with a critical evaluation of the strengths and limitations of the theory in question. Second, the emphasis in each chapter is on issues of clinical understanding and technique. Making extensive use of case material provided by each of the theorists, he shows how each object relations theory yields specific clinical approaches to a variety of syndromes, and how these approaches, in turn, entail specific modifications in clinical technique.Beyond his detailed attention to the theoretical and technical differences among object relations theories, Summers offers two concluding chapters that highlight the broad commonalities that link all object relations theories and set them apart from other contemporary approaches. His penultimate chapter discusses the similarities and differences of object relations and interpersonal theories. And his concluding chapter outlines a pragmatic object relations approach to development, psychopathology, and technique that combines elements of all object relations theories without opting for any single theory.Object Relations Theories and Psychopathology is that rare event in psychoanalytic publishing: a substantive, readable text that surveys a broad expanse of the theoretical and clinical landscape with erudition, sympathy, and critical perspective. It will be essential reading for all analysts, psychologists, psychiatrists, and social workers who wish to familiarize themselves with object relations theories in general, sharpen their understanding of the work of specific object relations theorists, or enhance their ability to employ these theories in their clinical work.},
	language = {en},
	publisher = {Analytic Press},
	author = {Summers, Frank},
	year = {1994},
	keywords = {vveitas:cognitive\_development},
	file = {Summers.1994.ObjectRelationsTheoryAndPsychopatology.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Summers.1994.ObjectRelationsTheoryAndPsychopatology.pdf:application/pdf}
}

@book{toit_making_2014,
	title = {Making {Sense} of {Coaching}},
	isbn = {978-1-4462-9729-2},
	abstract = {In her latest book, Angélique du Toit goes beyond the techniques and goals explored in most coaching texts to examine the process of coaching and the importance of sense-making for creating meaning and encouraging self-reflection. In doing this, the coaching experience emerges as a type of transformational learning, in which the individual is guided through a journey of discovery and revelation. Theories are drawn together in a fresh and original way which will cause readers to question how coaching should be defined and practised.   Dr Angélique du Toit is an academic practitioner and is involved in the delivery of academic programmes and publications related to coaching. She is also an Executive Coach supporting senior executives in their personal development in both the public and private sectors.  Electronic inspection copies are available for instructors.},
	language = {en},
	publisher = {SAGE},
	author = {Toit, Angelique Du},
	month = jan,
	year = {2014},
	file = {DuToit.2014.MakingSenseOfCoaching.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/DuToit.2014.MakingSenseOfCoaching.pdf:application/pdf}
}

@incollection{pask_organizational_1981,
	address = {North Holland, New York},
	title = {Organizational closure of potentially conscious systems},
	booktitle = {Autopoiesis: {A} {Theory} of {Living} {Organization}},
	author = {Pask, Gordon},
	editor = {Zeleny, Milan},
	year = {1981},
	file = {Pask.1981.OrganizationalClosureAndConsciousness.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Pask.1981.OrganizationalClosureAndConsciousness.pdf:application/pdf}
}

@article{van_overwalle_talking_2006,
	title = {Talking nets: a multiagent connectionist approach to communication and trust between individuals},
	volume = {113},
	issn = {0033-295X},
	shorttitle = {Talking nets},
	doi = {10.1037/0033-295X.113.3.606},
	abstract = {A multiagent connectionist model is proposed that consists of a collection of individual recurrent networks that communicate with each other and, as such, is a network of networks. The individual recurrent networks simulate the process of information uptake, integration, and memorization within individual agents, and the communication of beliefs and opinions between agents is propagated along connections between the individual networks. A crucial aspect in belief updating based on information from other agents is the trust in the information provided. In the model, trust is determined by the consistency with the receiving agents' existing beliefs and results in changes of the connections between individual networks, called trust weights. These weights lead to a selective propagation and thus to the filtering out of less reliable information, and they implement H. P. Grice's (1975) maxims of quality and quantity in communication. The unique contribution of communicative mechanisms beyond intrapersonal processing of individual networks was explored in simulations of key phenomena involving persuasive communication and polarization, lexical acquisition, spreading of stereotypes and rumors, and a lack of sharing unique information in group decisions.},
	language = {eng},
	number = {3},
	journal = {Psychological Review},
	author = {Van Overwalle, Frank and Heylighen, Francis},
	month = jul,
	year = {2006},
	pmid = {16802883},
	pages = {606--627},
	file = {Overwalle.Heylighen.2006.TalinkgNetsAMultiagentConnectionistApproach.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Overwalle.Heylighen.2006.TalinkgNetsAMultiagentConnectionistApproach.pdf:application/pdf}
}

@article{ono_self-maintenance_2000,
	title = {Self-maintenance and {Self}-reproduction in an {Abstract} {Cell} {Model}},
	volume = {206},
	issn = {0022-5193},
	url = {http://www.sciencedirect.com/science/article/pii/S0022519300921210},
	doi = {10.1006/jtbi.2000.2121},
	abstract = {Living cells must maintain their membranes by active metabolism. The membrane is not static but a dynamic structure that has evolved along with its internal reactions. When we reflect on the emergence and evolution of primitive cells, we should not forget the mutual dependency between membranes and metabolic cycles inside the cell. In this paper, we present a simple abstract model of the self-maintaining cell. A metabolic cycle will produce a self-assembling membrane that will enclose the metabolic cycle. We show that a self-maintaining cell has the potential to reproduce itself spontaneously. Further, we have demonstrated two different ways of cellular reproduction depending on the mobility of chemicals. In the first case, a cell releases autocatalytic chemicals that create new cells outside the mother cell. In the second case, a cell grows larger and divides itself into daughter cells by creating a new internal dividing membrane.},
	number = {2},
	urldate = {2014-08-14},
	journal = {Journal of Theoretical Biology},
	author = {ONO, NAOAKI and IKEGAMI, TAKASHI},
	month = sep,
	year = {2000},
	pages = {243--253},
	file = {Ono.2000.SelfMaintainanceAndSelfReproductinInAbstractCellModel.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Ono.2000.SelfMaintainanceAndSelfReproductinInAbstractCellModel.pdf:application/pdf}
}

@book{murphy_big_2004,
	address = {Cambridge, Mass.},
	title = {The {Big} {Book} of {Concepts}},
	isbn = {978-0-262-63299-7},
	abstract = {Concepts embody our knowledge of the kinds of things there are in the world. Tying our past experiences to our present interactions with the environment, they enable us to recognize and understand new objects and events. Concepts are also relevant to understanding domains such as social situations, personality types, and even artistic styles. Yet like other phenomenologically simple cognitive processes such as walking or understanding speech, concept formation and use are maddeningly complex.Research since the 1970s and the decline of the "classical view" of concepts have greatly illuminated the psychology of concepts. But persistent theoretical disputes have sometimes obscured this progress. The Big Book of Concepts goes beyond those disputes to reveal the advances that have been made, focusing on the major empirical discoveries. By reviewing and evaluating research on diverse topics such as category learning, word meaning, conceptual development in infants and children, and the basic level of categorization, the book develops a much broader range of criteria than is usual for evaluating theories of concepts.},
	language = {English},
	publisher = {A Bradford Book},
	author = {Murphy, Gregory},
	month = jan,
	year = {2004},
	file = {Murphy.2002.TheBigBookOfConcepts.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Murphy.2002.TheBigBookOfConcepts.pdf:application/pdf}
}

@article{murata_petri_1989,
	title = {Petri nets: {Properties}, analysis and applications},
	volume = {77},
	issn = {0018-9219},
	shorttitle = {Petri nets},
	doi = {10.1109/5.24143},
	abstract = {Starts with a brief review of the history and the application areas considered in the literature. The author then proceeds with introductory modeling examples, behavioral and structural properties, three methods of analysis, subclasses of Petri nets and their analysis. In particular, one section is devoted to marked graphs, the concurrent system model most amenable to analysis. Introductory discussions on stochastic nets with their application to performance modeling, and on high-level nets with their application to logic programming, are provided. Also included are recent results on reachability criteria. Suggestions are provided for further reading on many subject areas of Petri nets},
	number = {4},
	journal = {Proceedings of the IEEE},
	author = {Murata, T.},
	month = apr,
	year = {1989},
	pages = {541--580},
	file = {Murata.1989.PetriNetsPropertiesAnalysisAndApplications.pdf:/media/vveitas/LibraryKing/gdrive/vveitas@gmail.com/library/Murata.1989.PetriNetsPropertiesAnalysisAndApplications.pdf:application/pdf}
}

@book{morris_typogenetics:_1989,
	title = {Typogenetics: {A} {Logic} of {Artificial} {Propagating} {Entities}},
	shorttitle = {Typogenetics},
	language = {en},
	publisher = {University of British Columbia},
	author = {Morris, Harold Campbell},
	year = {1989},
	file = {Morris.Typogenetics1989.pdf:/media/vveitas/LibraryKing/gdrive/vveitas@gmail.com/library/Morris.Typogenetics1989.pdf:application/pdf}
}

@inproceedings{mcmullin_towards_2001,
	title = {Towards the {Implementation} of {Evolving} {Autopoietic} {Artificial} {Agents}},
	abstract = {We report modifications to the SCL model(McMullin and Varela, 1997), an artificial chemistry in Swarm designed to support autopoietic agents. The aim of these modifications is to improve on the longevity of the agents and to implement growth. We demonstrate by means of two simulation runs that the improvements indeed have the desired effects. 1 Background: SCL A computational model of autopoiesis was originally described by Varela et al. (1974). This was re-implemented by McMullin in Swarm 1 as the SCL system (McMullin and Varela, 1997; McMullin, 1997). SCL contains three different types of particles: substrate (S), catalyst (C) and links (L). In this model an autopoietic agent or organisation consists of a closed (self-repairing) chain of doubly bonded links which encloses a C particle. In order to qualify as an interesting instance of autopoiesis, its longevity has to exceed that of its components (the links) which are designed to be unstable. In the experiments presented in (McMullin and Varela, 1997) the minimal autopoietic organisation could be sustained for up to approximately 1800 time-steps, but was eventually irreparably corrupted by some decaying links which could not be replaced quickly enough.},
	booktitle = {Advances in {Artificial} {Life}, {Proceedings} of the 6th {European} {Conference}},
	publisher = {Springer},
	author = {Mcmullin, Barry and Groß, Dominique},
	year = {2001},
	pages = {440--443},
	file = {McMullin.2001.TowardsTheImplementationOfEvolvingAutopoieticArtificialAgents.pdf:/media/vveitas/LibraryKing/gdrive/vveitas@gmail.com/library/McMullin.2001.TowardsTheImplementationOfEvolvingAutopoieticArtificialAgents.pdf:application/pdf}
}

@book{mcmullin_rediscovering_1997,
	title = {Rediscovering {Computational} {Autopoiesis}},
	abstract = {This paper summarises some initial empirical results from a new computer model (artificial chemistry) which exhibits spontaneous emergence and persistence of autopoietic organisation. The model is based on a system originally presented by Varela, Maturana and Uribe [8]. In carrying out this re-implementation it was found that an additional interaction (chain-based bond inhibition) , not documented in the original description by Varela et al., is critical to the realisation of the autopoietic phenomena. This required interaction was re-discovered only following careful examination of (unpublished) source code for an early version of the original model. The purpose of the paper is thus twofold: firstly to identify and discuss this previously undocumented, but essential, interaction; and secondly to argue, on the basis of this particular case, for the importance of exploiting the emerging technologies which support publication of completely detailed software models (in addition, of course...},
	author = {McMullin, Barry and Varela, Francisco J.},
	year = {1997},
	file = {McMullin.1997.RediscoveringComputationalAutopoiesis.pdf:/media/vveitas/LibraryKing/gdrive/vveitas@gmail.com/library/McMullin.1997.RediscoveringComputationalAutopoiesis.pdf:application/pdf}
}

@article{misra_design_2009,
	title = {Design of a {P} {System} based {Artificial} {Graph} {Chemistry}},
	url = {http://arxiv.org/abs/0901.0317},
	abstract = {Artificial Chemistries (ACs) are symbolic chemical metaphors for the exploration of Artificial Life, with specific focus on the origin of life. In this work we define a P system based artificial graph chemistry to understand the principles leading to the evolution of life-like structures in an AC set up and to develop a unified framework to characterize and classify symbolic artificial chemistries by devising appropriate formalism to capture semantic and organizational information. An extension of P system is considered by associating probabilities with the rules providing the topological framework for the evolution of a labeled undirected graph based molecular reaction semantics.},
	urldate = {2014-08-14},
	journal = {arXiv:0901.0317 [cs]},
	author = {Misra, Janardan},
	month = jan,
	year = {2009},
	note = {arXiv: 0901.0317},
	file = {Misra.2009.DesignOfAPSystemBasedArtificialGraphChemistry.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Misra.2009.DesignOfAPSystemBasedArtificialGraphChemistry.pdf:application/pdf}
}

@book{fodor_self-expansion_nodate,
	title = {Self-expansion - redefining key psychology terms with system theory},
	isbn = {978-1-4092-9459-7},
	language = {en},
	publisher = {Psychology 2.0 Books},
	author = {Fodor, Miklos},
	file = {Fodor.2009.SelfExpansion.RedefiningKeyPsychologyTermsWithSystemTheory.pdf:/media/vveitas/LibraryKing/gdrive/vveitas@gmail.com/library/Fodor.2009.SelfExpansion.RedefiningKeyPsychologyTermsWithSystemTheory.pdf:application/pdf}
}

@article{varela_autopoiesis:_1974,
	title = {Autopoiesis: the organization of living systems, its characterization and a model},
	volume = {5},
	number = {4},
	journal = {Biosystems},
	author = {Varela, Francisco G and Maturana, Humberto R and Uribe, Ricardo},
	year = {1974},
	keywords = {vveitas:generative\_model, vveitas:vienna2015},
	pages = {187--196},
	file = {Maturana.1974.AutopoiesisTheOrganizationOfLivingSystems.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Maturana.1974.AutopoiesisTheOrganizationOfLivingSystems.pdf:application/pdf}
}

@article{maturana_autopoiesis_2002,
	title = {Autopoiesis, {Structural} {Coupling} and {Cognition}: {A} history of these and other notions in the biology of cognition},
	volume = {9},
	shorttitle = {Autopoiesis, {Structural} {Coupling} and {Cognition}},
	abstract = {My intent in this essay is to reflect on the history of some biological notions such as autopoiesis, structural coupling, and cognition, that I have developed since the early 1960's as a result of my work on visual perception and the organization of the living. No doubt I shall repeat things that I have said in other publications (Maturana \& Varela, 1980, 1988), and I shall present notions that once they are said appear as obvious truisms. Moreover, I shall refine or expand the meaning of such notions, or even modify them. Yet, in any case, the reader is not invited to attend to the truisms, or to what seems to be obvious, rather he or she is invited to attend to the consequences that those notions entail for the understanding of cognition as a biological process. After all, explanations or demonstrations always become self evident once they are understood and accepted, and the purpose of this essay is the expansion of understanding in all dimensions of human existence.},
	number = {3-4},
	journal = {Cybernetics \& Human Knowing},
	author = {Maturana, H.},
	month = mar,
	year = {2002},
	pages = {5--34},
	file = {Maturana.2002.AutopoiesisStructuralCouplingAnCognition.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Maturana.2002.AutopoiesisStructuralCouplingAnCognition.pdf:application/pdf}
}

@article{martin_self-assembly_2010,
	title = {Self-assembly of neural networks viewed as},
	volume = {4},
	issn = {1935-3812, 1935-3820},
	url = {http://link.springer.com/article/10.1007/s11721-009-0035-7},
	doi = {10.1007/s11721-009-0035-7},
	abstract = {While self-assembly is a fairly active area of research in swarm intelligence, relatively little attention has been paid to the issues surrounding the construction of network structures. In this paper we extend methods developed previously for controlling collective movements of agent teams to serve as the basis for self-assembly or “growth” of networks, using neural networks as a concrete application to evaluate our approach. Our central innovation is having network connections arise as persistent “trails” left behind moving agents, trails that are reminiscent of pheromone deposits made by agents in ant colony optimization models. The resulting network connections are thus essentially a record of agent movements. We demonstrate our model’s effectiveness by using it to produce two large networks that support subsequent learning of topographic and feature maps. Improvements produced by the incorporation of collective movements are also examined through computational experiments. These results indicate that methods for directing collective movements can be adopted to facilitate network self-assembly.},
	language = {en},
	number = {1},
	urldate = {2014-08-13},
	journal = {Swarm Intelligence},
	author = {Martin, Charles E. and Reggia, James A.},
	month = mar,
	year = {2010},
	pages = {1--36},
	file = {Martin.Reggia.2010.Self-assemblyOfNeuralNetworksViewedAsSwarmIntelligence.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Martin.Reggia.2010.Self-assemblyOfNeuralNetworksViewedAsSwarmIntelligence.pdf:application/pdf}
}

@inproceedings{kahn_semantics_1974,
	title = {The {Semantics} of {Simple} {Language} for {Parallel} {Programming}.},
	url = {http://dblp.uni-trier.de/db/conf/ifip/ifip74.html#Kahn74},
	booktitle = {{IFIP} {Congress}},
	author = {Kahn, Gilles},
	year = {1974},
	keywords = {vveitas:distributed\_systems},
	pages = {471--475},
	file = {Kahn.1974.TheSemanticsOfASimpleLanguageForParallelProgramming.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Kahn.1974.TheSemanticsOfASimpleLanguageForParallelProgramming.pdf:application/pdf}
}

@article{gallo_directed_1993,
	title = {Directed {Hypergraphs} and {Applications}},
	volume = {42},
	issn = {0166-218X},
	url = {http://dx.doi.org/10.1016/0166-218X(93)90045-P},
	doi = {10.1016/0166-218X(93)90045-P},
	number = {2-3},
	urldate = {2014-08-13},
	journal = {Discrete Appl. Math.},
	author = {Gallo, Giorgio and Longo, Giustino and Pallottino, Stefano and Nguyen, Sang},
	month = apr,
	year = {1993},
	pages = {177--201},
	file = {Gallo.EtAl.1993.DirectedHypergraphsAndApplications.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Gallo.EtAl.1993.DirectedHypergraphsAndApplications.pdf:application/pdf}
}

@phdthesis{hoffmann_structural_2006,
	title = {Structural {Coupling} {With} {Environment} and it modelling on neural driven agents},
	author = {Hoffmann, Matej},
	year = {2006},
	file = {Hoffmann.2006.StructuralCouplingWithEnviromnentMasterThesis.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Hoffmann.2006.StructuralCouplingWithEnviromnentMasterThesis.pdf:application/pdf}
}

@book{heylighen_representation_1990,
	title = {Representation and {Change}: {A} {Metarepresentational} {Framework} for the {Foundations} of {Physical} and {Cognitive} {Science}},
	shorttitle = {Representation and {Change}},
	language = {en},
	publisher = {Communication \& Cognition},
	author = {Heylighen, Francis},
	year = {1990},
	file = {Heylighen.1989.RepresentationAndChange.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.1989.RepresentationAndChange.pdf:application/pdf}
}

@misc{heylighen_chemical_2012,
	title = {Chemical {Organization} {Theory}: a formalism for evolutionary cybernetics},
	author = {Heylighen, Francis},
	month = jul,
	year = {2012},
	file = {Heylighen.2012.mail_cot20120730.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.2012.mail_cot20120730.pdf:application/pdf}
}

@unpublished{heylighen_challange_2012,
	type = {{GBI} {Working} {Paper}},
	title = {Challange {Propagation}: a new paradigm for modeling distributed intelligence},
	url = {http://pespmc1.vub.ac.be/Papers/ChallengePropagation.pdf},
	author = {Heylighen, Francis},
	year = {2012},
	file = {Heylighen.2012.ChallengePropagation.GBIWorkingPaper.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.2012.ChallengePropagation.GBIWorkingPaper.pdf:application/pdf}
}

@article{heylighen_causality_1989-1,
	title = {Causality {As} {Distinction} {Conservation}: {A} {Theory} of {Predictability}, {Reversibility}, and {Time} {Order}},
	volume = {20},
	issn = {0196-9722},
	shorttitle = {Causality {As} {Distinction} {Conservation}},
	url = {http://dx.doi.org/10.1080/01969728908902213},
	doi = {10.1080/01969728908902213},
	number = {5},
	urldate = {2014-08-13},
	journal = {Cybern. Syst.},
	author = {Heylighen, Francis},
	month = dec,
	year = {1989},
	pages = {361--384},
	file = {Heylighen.1989.CausalityAsDistinctionConservation.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.1989.CausalityAsDistinctionConservation.pdf:application/pdf}
}

@inproceedings{heylighen_world-wide_1996,
	title = {The {World}-{Wide} {Web} as a {Super}-{Brain}: from metaphor to model},
	shorttitle = {The {World}-{Wide} {Web} as a {Super}-{Brain}},
	abstract = {Abstract ticular has been characterized by the explosive develop-If society is viewed as a super-organism, communication networks play the role of its brain. This metaphor is developed into a model for the design of a more intelligent global network. The World-Wide Web, through its distributed hypermedia architecture, functions as an “associative memory”, which may “learn ” by the strengthening of frequently used links. Software agents, exploring the Web through spreading activation, function as problem-solving “thoughts”. Users are integrated into this \"super-brain \" through direct manmachine interfaces and the reciprocal exchange of knowledge between individual and Web. 1},
	booktitle = {Cybernetics and {Systems} '96. {R}. {Trappl} ({Ed}.). {Austrian} {Society} {For} {Cybernetics}},
	publisher = {Press},
	author = {Heylighen, Francis and Bollen, Johan},
	year = {1996},
	pages = {917--922},
	file = {Heylighen.Bollen.1996.TheWorldWideWebAsASuperBrain.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.Bollen.1996.TheWorldWideWebAsASuperBrain.pdf:application/pdf}
}

@article{heylighen_global_2002-1,
	title = {The {Global} {Superorganism}: an evolutionary-cybernetic model of the emerging network society},
	journal = {Journal of Social and Evolutionary Systems},
	author = {Heylighen, Francis},
	year = {2002},
	file = {Heylighen.2002.TheGlobalSuperorganism.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.2002.TheGlobalSuperorganism.pdf:application/pdf}
}

@article{heylighen_conceptions_2011,
	title = {Conceptions of a {Global} {Brain}: an historical review},
	journal = {Evolution: Cosmic, Biological, and Social, eds. Grinin, LE, Carneiro, RL, Korotayev AV, Spier F},
	author = {Heylighen, Francis},
	year = {2011},
	pages = {274--289},
	file = {Heylighen.2011.ConceptionsOfTheGlobalBrain.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.2011.ConceptionsOfTheGlobalBrain.pdf:application/pdf}
}

@unpublished{heylighen_coognitive_2009,
	address = {Brussels},
	title = {Coognitive {Systems}: {A} {Cybernetic} {Perspective} {On} {The} {New} {Science} {Of} {Mind}},
	url = {http://pespmc1.vub.ac.be/CLEA/CognSysCursus.pdf},
	author = {Heylighen, Francis},
	year = {2009},
	file = {Heylighen.2009.CognitiveSystems.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.2009.CognitiveSystems.pdf:application/pdf}
}

@book{hawkins_intelligence_2005,
	address = {New York},
	title = {On {Intelligence}},
	isbn = {0-8050-7853-3},
	abstract = {From the inventor of the PalmPilot comes a new and compelling theory of intelligence, brain function, and the future of intelligent machinesJeff Hawkins, the man who created the PalmPilot, Treo smart phone, and other handheld devices, has reshaped our relationship to computers. Now he stands ready to revolutionize both neuroscience and computing in one stroke, with a new understanding of intelligence itself.Hawkins develops a powerful theory of how the human brain works, explaining why computers are not intelligent and how, based on this new theory, we can finally build intelligent machines.The brain is not a computer, but a memory system that stores experiences in a way that reflects the true structure of the world, remembering sequences of events and their nested relationships and making predictions based on those memories. It is this memory-prediction system that forms the basis of intelligence, perception, creativity, and even consciousness.In an engaging style that will captivate audiences from the merely curious to the professional scientist, Hawkins shows how a clear understanding of how the brain works will make it possible for us to build intelligent machines, in silicon, that will exceed our human ability in surprising ways.Written with acclaimed science writer Sandra Blakeslee, On Intelligence promises to completely transfigure the possibilities of the technology age. It is a landmark book in its scope and clarity.},
	language = {English},
	publisher = {St. Martin's Griffin},
	author = {Hawkins, Jeff and Blakeslee, Sandra},
	month = jul,
	year = {2005},
	file = {Hawkins.2005.OnIntelligence.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Hawkins.2005.OnIntelligence.pdf:application/pdf}
}

@book{bodenhamer_users_2003,
	address = {Carmarthen, Wales ; Williston, VT},
	title = {User's {Manual} for the {Brain}: {Vol}. {II}, {Mastering} {Systemic} {NLP}},
	isbn = {978-1-899836-88-8},
	shorttitle = {User's {Manual} for the {Brain}},
	abstract = {Following on from Volume I, this is the most comprehensive manual published to date covering the NLP Master Practitioner course. The authors introduce some of the newer advancements in the field and invite you to go beyond the Practitioner level and on to the Master s level where you will not only understand NLP, but you will be able to develop the very spirit of NLP. In addition, this volume also introduces the reader to: Advanced Meta-Model Distinctions, Mind-Lines, Advanced Time-Line Patterns, and Meta-Domains Systemic Models. Packed with case studies, seminar demonstrations, discussions, and trances, this volume will enable the practitioner to develop an attitude and spirit that allows them to apply the NLP Model powerfully.},
	language = {English},
	publisher = {Crown House Publishing},
	author = {Bodenhamer, L. Michael Hall \& Bob G.},
	month = apr,
	year = {2003},
	file = {Hall.Bodenhamer.2003.TheUsersManualForTheBrainVol2.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Hall.Bodenhamer.2003.TheUsersManualForTheBrainVol2.pdf:application/pdf}
}

@book{haikonen_robot_2007,
	address = {Chichester, England ; Hoboken, NJ},
	edition = {1 edition},
	title = {Robot {Brains}: {Circuits} and {Systems} for {Conscious} {Machines}},
	isbn = {978-0-470-06204-3},
	shorttitle = {Robot {Brains}},
	abstract = {Haikonen envisions autonomous robots that perceive and understand the world directly, acting in it in a natural human-like way without the need of programs and numerical representation of information. By developing higher-level cognitive functions through the power of artificial associative neuron architectures, the author approaches the issues of machine consciousness.Robot Brains expertly outlines a complete system approach to cognitive machines, offering practical design guidelines for the creation of non-numeric autonomous creative machines. It details topics such as component parts and realization principles, so that different pieces may be implemented in hardware or software. Real-world examples for designers and researchers are provided, including circuit and systems examples that few books on this topic give.In novel technical and practical detail, this book also considers:the limitations and remedies of traditional neural associators in creating true machine cognition;basic circuit assemblies cognitive neural architectures;how motors can be interfaced with the associative neural system in order for fluent motion to be achieved without numeric computations;memorization, imagination, planning and reasoning in the machine;the concept of machine emotions for motivation and value systems;an approach towards the use and understanding of natural language in robots.The methods presented in this book have important implications for computer vision, signal processing, speech recognition and other information technology fields. Systematic and thoroughly logical, it will appeal to practising engineers involved in the development and design of robots and cognitive machines, also researchers in Artificial Intelligence. Postgraduate students in computational neuroscience and robotics, and neuromorphic engineers will find it an exciting source of information.},
	language = {English},
	publisher = {Wiley-Interscience},
	author = {Haikonen, Pentti O.},
	month = oct,
	year = {2007},
	file = {Haikonen.2007.RobotBrains CircuitsAndSystemsForConsciousMachines.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Haikonen.2007.RobotBrains CircuitsAndSystemsForConsciousMachines.pdf:application/pdf}
}

@book{haggstrom_finite_2002,
	address = {Cambridge ; New York},
	edition = {1 edition},
	title = {Finite {Markov} {Chains} and {Algorithmic} {Applications}},
	isbn = {978-0-521-89001-4},
	abstract = {This text is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before using it to study a range of randomized algorithms with important applications in optimization and other problems in computing. The book will appeal not only to mathematicians, but to students of computer science who will discover much useful material. This clear and concise introduction to the subject has numerous exercises that will help students to deepen their understanding.},
	language = {English},
	publisher = {Cambridge University Press},
	author = {Häggström, Olle},
	month = jun,
	year = {2002},
	file = {Haggstrom.2202.FiniteMarkovChainsAndAlgorithmicApplications.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Haggstrom.2202.FiniteMarkovChainsAndAlgorithmicApplications.pdf:application/pdf}
}

@inproceedings{gregg_where_2011,
	title = {Where is the data? {Why} you cannot debate {CPU} vs. {GPU} performance without the answer},
	shorttitle = {Where is the data?},
	doi = {10.1109/ISPASS.2011.5762730},
	abstract = {General purpose GPU Computing (GPGPU) has taken off in the past few years, with great promises for increased desktop processing power due to the large number of fast computing cores on high-end graphics cards. Many publications have demonstrated phenomenal performance and have reported speedups as much as 1000× over code running on multi-core CPUs. Other studies have claimed that well-tuned CPU code reduces the performance gap significantly. We demonstrate that this important discussion is missing a key aspect, specifically the question of where in the system data resides, and the overhead to move the data to where it will be used, and back again if necessary. We have benchmarked a broad set of GPU kernels on a number of platforms with different GPUs and our results show that when memory transfer times are included, it can easily take between 2 to 50× longer to run a kernel than the GPU processing time alone. Therefore, it is necessary to either include memory transfer overhead when reporting GPU performance, or to explain why this is not relevant for the application in question. We suggest a taxonomy for future CPU/GPU comparisons, and we argue that this is not only germane for reporting performance, but is important to heterogeneous scheduling research in general.},
	booktitle = {2011 {IEEE} {International} {Symposium} on {Performance} {Analysis} of {Systems} and {Software} ({ISPASS})},
	author = {Gregg, C. and Hazelwood, K.},
	month = apr,
	year = {2011},
	pages = {134--144},
	file = {Gregg.2011.WhereIsTheDataWhyYouCannotDebateCPUvsGPUPerformanceWithoutTheAnswer.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Gregg.2011.WhereIsTheDataWhyYouCannotDebateCPUvsGPUPerformanceWithoutTheAnswer.pdf:application/pdf}
}

@article{kowalik_parallel_2012,
	title = {Parallel optimization of synthetic pathways within the network of organic chemistry},
	volume = {51},
	issn = {1521-3773},
	doi = {10.1002/anie.201202209},
	language = {eng},
	number = {32},
	journal = {Angewandte Chemie (International Ed. in English)},
	author = {Kowalik, Mikołaj and Gothard, Chris M. and Drews, Aaron M. and Gothard, Nosheen A. and Weckiewicz, Alex and Fuller, Patrick E. and Grzybowski, Bartosz A. and Bishop, Kyle J. M.},
	month = aug,
	year = {2012},
	pmid = {22807100},
	pages = {7928--7932},
	file = {Kowalik.2012.ParallelOptimizationOfSyntheticPathwaysWithinTheNetworkOfOrganicChemistry.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Kowalik.2012.ParallelOptimizationOfSyntheticPathwaysWithinTheNetworkOfOrganicChemistry.pdf:application/pdf}
}

@article{gothard_rewiring_2012,
	title = {Rewiring {Chemistry}: {Algorithmic} {Discovery} and {Experimental} {Validation} of {One}-{Pot} {Reactions} in the {Network} of {Organic} {Chemistry}},
	volume = {51},
	copyright = {Copyright © 2012 WILEY-VCH Verlag GmbH \& Co. KGaA, Weinheim},
	issn = {1521-3773},
	shorttitle = {Rewiring {Chemistry}},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/anie.201202155/abstract},
	doi = {10.1002/anie.201202155},
	language = {en},
	number = {32},
	urldate = {2014-08-13},
	journal = {Angewandte Chemie International Edition},
	author = {Gothard, Chris M. and Soh, Siowling and Gothard, Nosheen A. and Kowalczyk, Bartlomiej and Wei, Yanhu and Baytekin, Bilge and Grzybowski, Bartosz A.},
	month = aug,
	year = {2012},
	pages = {7922--7927},
	file = {Gothard.2012.RewiringChemistryAlgorithmicDiscoveryAndExperimentalValidationInTheNetworkOfOrganicChemistry.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Gothard.2012.RewiringChemistryAlgorithmicDiscoveryAndExperimentalValidationInTheNetworkOfOrganicChemistry.pdf:application/pdf}
}

@article{fuller_chemical_2012,
	title = {Chemical {Network} {Algorithms} for the {Risk} {Assessment} and {Management} of {Chemical} {Threats}},
	volume = {51},
	copyright = {Copyright © 2012 WILEY-VCH Verlag GmbH \& Co. KGaA, Weinheim},
	issn = {1521-3773},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/anie.201202210/abstract},
	doi = {10.1002/anie.201202210},
	language = {en},
	number = {32},
	urldate = {2014-08-13},
	journal = {Angewandte Chemie International Edition},
	author = {Fuller, Patrick E. and Gothard, Chris M. and Gothard, Nosheen A. and Weckiewicz, Alex and Grzybowski, Bartosz A.},
	month = aug,
	year = {2012},
	pages = {7933--7937},
	file = {Fuller.2012.ChemicalNetworkAlgorithmsForTheRiskAssessmentAndManagementOfChemicalThreats.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Fuller.2012.ChemicalNetworkAlgorithmsForTheRiskAssessmentAndManagementOfChemicalThreats.pdf:application/pdf}
}

@unpublished{goertzel_ii._2012,
	title = {{II}. {Perception} {Processing} for {General} {Intelligence}, {Part} {II}: {Bridging} the {Symbolic}/{Subsymbolic} {Gap}},
	author = {Goertzel, Ben},
	month = jul,
	year = {2012},
	file = {Goertzel.2012.PerceptionProcessingPart2BridgingSymbolicSubsymbolicGap.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Goertzel.2012.PerceptionProcessingPart2BridgingSymbolicSubsymbolicGap.pdf:application/pdf}
}

@unpublished{goertzel_i._2012,
	title = {I. {Perception} {Processing} for {General} {Intelligence}, {Part} {I}: {Representationally} {Transparent} {Deep} {Learning}},
	author = {Goertzel, Ben},
	month = jul,
	year = {2012},
	file = {Goertzel.2012.PerceptionProcessing1DeepLearning.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Goertzel.2012.PerceptionProcessing1DeepLearning.pdf:application/pdf}
}

@inproceedings{goertzel_novel_2011,
	title = {A {Novel} {Strategy} for {Hybridizing} {Subsymbolic} and {Symbolic} {Learning} and {Representation}},
	booktitle = {{AAAI} {Fall} {Symposium}: {Advances} in {Cognitive} {Systems}'11},
	author = {Goertzel, Ben},
	year = {2011},
	pages = {--1--1}
}

@book{goertzel_biological_2004,
	title = {On {Biological} and {Digital} {Intelligence}},
	url = {http://www.goertzel.org/dynapsyc/2004/OnBiologicalAndDigitalIntelligence.htm},
	author = {Goertzel, Ben},
	month = oct,
	year = {2004},
	file = {Goertzel.2004.OnBiologicalAndDigitalIntelligence.BlogPost.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Goertzel.2004.OnBiologicalAndDigitalIntelligence.BlogPost.pdf:application/pdf}
}

@book{gershenson_design_2007,
	title = {Design and {Control} of {Self}-organizing {Systems}},
	isbn = {978-0-9831172-3-0},
	abstract = {Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this book I propose a methodology to aid engineers in the design and control of complex systems. This is based on the description of systems as self-organizing. Starting from the agent metaphor, the methodology proposes a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by actively interacting among themselves.},
	language = {en},
	publisher = {CopIt ArXives},
	author = {Gershenson, Carlos},
	month = sep,
	year = {2007},
	file = {Gershenson.2007.DesignAndControlOfSelfOrganizingSystems.pdf:/home/kabir/vveitas@gmail.com/library/Gershenson.2007.DesignAndControlOfSelfOrganizingSystems.pdf:application/pdf}
}

@article{gershenson_sigma_2011,
	title = {The sigma profile: {A} formal tool to study organization and its evolution at multiple scales},
	volume = {16},
	copyright = {Copyright © 2010 Wiley Periodicals, Inc.},
	issn = {1099-0526},
	shorttitle = {The sigma profile},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/cplx.20350/abstract},
	doi = {10.1002/cplx.20350},
	abstract = {The σ profile is presented as a tool to analyze the organization of systems at different scales, and how this organization changes in time. Describing structures at different scales as goal-oriented agents, one can define σ ∈ [0,1] (satisfaction) as the degree to which the goals of each agent at each scale have been met. σ reflects the organization degree at that scale. The σ profile of a system shows the satisfaction at different scales, with the possibility to study their dependencies and evolution. It can also be used to extend game theoretic models. The description of a general tendency on the evolution of complexity and cooperation naturally follows from the σ profile. Experiments on a virtual ecosystem are used as illustration.},
	language = {en},
	number = {5},
	urldate = {2014-08-12},
	journal = {Complexity},
	author = {Gershenson, Carlos},
	month = may,
	year = {2011},
	pages = {37--44},
	file = {Gershenson.2008.TheSigmaProfileAFormalToolToStudyOrganizationAndItsEvolutionAtMultipleScales.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Gershenson.2008.TheSigmaProfileAFormalToolToStudyOrganizationAndItsEvolutionAtMultipleScales.pdf:application/pdf}
}

@article{gershenson_general_2005,
	title = {A {General} {Methodology} for {Designing} {Self}-{Organizing} {Systems}},
	url = {http://arxiv.org/abs/nlin/0505009},
	abstract = {Our technologies complexify our environments. Thus, new technologies need to deal with more and more complexity. Several efforts have been made to deal with this complexity using the concept of self-organization. However, in order to promote its use and understanding, we must first have a pragmatic understanding of complexity and self-organization. This paper presents a conceptual framework for speaking about self-organizing systems. The aim is to provide a methodology useful for designing and controlling systems developed to solve complex problems. First, practical notions of complexity and self-organization are given. Then, starting from the agent metaphor, a conceptual framework is presented. This provides formal ways of speaking about "satisfaction" of elements and systems. The main premise of the methodology claims that reducing the "friction" or "interference" of interactions between elements of a system will result in a higher "satisfaction" of the system, i.e. better performance. The methodology discusses different ways in which this can be achieved. A case study on self-organizing traffic lights illustrates the ideas presented in the paper.},
	urldate = {2014-08-12},
	journal = {arXiv:nlin/0505009},
	author = {Gershenson, Carlos},
	month = may,
	year = {2005},
	note = {arXiv: nlin/0505009},
	file = {Gershenson.2006.AGeneralMethodologyForDesingSelfOrganizingSystems.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Gershenson.2006.AGeneralMethodologyForDesingSelfOrganizingSystems.pdf:application/pdf}
}

@article{gershenson_computing_2010,
	title = {Computing {Networks}: {A} {General} {Framework} to {Contrast} {Neural} and {Swarm} {Cognitions}},
	volume = {1},
	issn = {2080-9778, 2081-4836},
	shorttitle = {Computing {Networks}},
	url = {http://arxiv.org/abs/1001.5244},
	doi = {10.2478/s13230-010-0015-z},
	abstract = {This paper presents the Computing Networks (CNs) framework. CNs are used to generalize neural and swarm architectures. Artificial neural networks, ant colony optimization, particle swarm optimization, and realistic biological models are used as examples of instantiations of CNs. The description of these architectures as CNs allows their comparison. Their differences and similarities allow the identification of properties that enable neural and swarm architectures to perform complex computations and exhibit complex cognitive abilities. In this context, the most relevant characteristics of CNs are the existence multiple dynamical and functional scales. The relationship between multiple dynamical and functional scales with adaptation, cognition (of brains and swarms) and computation is discussed.},
	number = {2},
	urldate = {2014-08-12},
	journal = {Paladyn},
	author = {Gershenson, Carlos},
	month = jun,
	year = {2010},
	note = {arXiv: 1001.5244},
	pages = {147--153},
	file = {Gershenson.2010.ComputingNetworksAGeneralFrameworkToContrastNeuralAndSwarmCognitions.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Gershenson.2010.ComputingNetworksAGeneralFrameworkToContrastNeuralAndSwarmCognitions.pdf:application/pdf}
}

@article{gershenson_cognitive_2004,
	title = {Cognitive {Paradigms}: {Which} {One} is the {Best}?},
	volume = {5},
	issn = {1389-0417},
	shorttitle = {Cognitive {Paradigms}},
	url = {http://dx.doi.org/10.1016/j.cogsys.2003.10.002},
	doi = {10.1016/j.cogsys.2003.10.002},
	abstract = {I discuss the suitability of different paradigms for studying cognition. I use a virtual laboratory that implements five different representative models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no ''best'' model, since different models are better for different things in different contexts. Using the results as an empirical philosophical aid, I note that there is no ''best'' approach for studying cognition, since different paradigms have all advantages and disadvantages, since they study different aspects of cognition from different contexts. This has implications for current debates on ''proper'' approaches for cognition: all approaches are a bit proper, but none will be ''proper enough''. I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition.},
	number = {2},
	urldate = {2014-08-12},
	journal = {Cogn. Syst. Res.},
	author = {Gershenson, Carlos},
	month = jun,
	year = {2004},
	pages = {135--156},
	file = {Gershenson.2003.CognitiveParadigmsWhichOneIsTheBest.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Gershenson.2003.CognitiveParadigmsWhichOneIsTheBest.pdf:application/pdf}
}

@book{noauthor_functional_nodate,
	title = {Functional {Programming} for {Java} {Developers}},
	url = {http://shop.oreilly.com/product/0636920021667.do},
	abstract = {Software development today is embracing functional programming (FP), whether it’s to write concurrent programs or to manage Big Data. Where does that leave Java developers? This concise book offers a pragmatic, approachable introduction to FP...},
	urldate = {2014-08-12},
	file = {Wampler.2011.Functional.Programming.for.Java.Developers.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Wampler.2011.Functional.Programming.for.Java.Developers.pdf:application/pdf}
}

@mastersthesis{speroni_di_fenizio_building_1999,
	title = {Building {Life} {Without} {Cheating}},
	author = {Speroni di Fenizio, Pietro},
	year = {1999},
	file = {Fenisio.BuildingLifeWithoutCheating.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Fenisio.BuildingLifeWithoutCheating.pdf:application/pdf}
}

@article{speroni_di_fenizio_spontaneous_2001,
	title = {Spontaneous formation of proto-cells in an universal artificial chemistry on a planar graph},
	journal = {Advances in artificial life},
	author = {Speroni di Fenizio, Pietro and Dittrich, Peter and Banzhaf, Wolfgang},
	year = {2001},
	pages = {206--215},
	file = {DiFenizio.etAl.SpontaneousFormationOfProtoCellsInAnUniversalArtificialChemistyOnAPlanarGraph.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/DiFenizio.etAl.SpontaneousFormationOfProtoCellsInAnUniversalArtificialChemistyOnAPlanarGraph.pdf:application/pdf}
}

@article{speroni_di_fenizio_stability_2001,
	title = {Stability of metabolic and balanced organisations},
	journal = {Advances in artificial life},
	author = {Speroni di Fenizio, Pietro and Banzhaf, Wolfgang},
	year = {2001},
	pages = {196--205},
	file = {DiFenisio.StabilityOfMetabolicAndBalancedOrganizations.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/DiFenisio.StabilityOfMetabolicAndBalancedOrganizations.pdf:application/pdf}
}

@book{delanda_philosophy_2011,
	title = {Philosophy and {Simulation}: {The} {Emergence} of {Synthetic} {Reason}},
	isbn = {978-1-4411-7028-6},
	shorttitle = {Philosophy and {Simulation}},
	abstract = {\>},
	language = {en},
	publisher = {A\&C Black},
	author = {DeLanda, Manuel},
	month = mar,
	year = {2011},
	keywords = {vveitas:generative\_model, vveitas:social\_cognition},
	file = {DeLanda.2011.PhilosophyAndSimulation.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/DeLanda.2011.PhilosophyAndSimulation.pdf:application/pdf}
}

@misc{davies_summary_nodate,
	title = {Summary on {Hofstadler}'s {Fluid} {Concepts} and {Creative} {Analogies}},
	url = {http://www.jimdavies.org/summaries/hofstadter1995.html},
	author = {Davies, Jim},
	file = {Davies.2002.OnHofstadlersCopycat.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Davies.2002.OnHofstadlersCopycat.pdf:application/pdf}
}

@techreport{datomic_datomic:_2012,
	title = {Datomic: {Technical} {Overview}},
	urldate = {2012-05-05},
	author = {Datomic},
	year = {2012},
	file = {Datomic.2012.Datomic.TechnicalOverview.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Datomic.2012.Datomic.TechnicalOverview.pdf:application/pdf}
}

@misc{busseniers_hierarchical_2012,
	title = {Hierarchical organization versus self-organization},
	language = {English},
	publisher = {GBI working paper},
	author = {Busseniers, Evo},
	month = apr,
	year = {2012},
	file = {Busseniers.2012.HierarchicalOrganizationVersusSelf-Organization.WorkingPaper.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Busseniers.2012.HierarchicalOrganizationVersusSelf-Organization.WorkingPaper.pdf:application/pdf}
}

@article{bollen_cognitive_2001,
	title = {A cognitive model of adaptive web design and navigation: a shared knowledge perspective},
	journal = {Unpublished doctoral dissertation. Faculty of Psychology, Free University of Brussels},
	author = {Bollen, Johan},
	year = {2001},
	file = {Bollen.2001.AcognitiveModelOfAdaptiveWebDesignAndNavigation.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Bollen.2001.AcognitiveModelOfAdaptiveWebDesignAndNavigation.pdf:application/pdf}
}

@article{brooks_choosing_1996,
	title = {Choosing the best model: {Level} of detail, complexity, and model performance},
	volume = {24},
	issn = {0895-7177},
	shorttitle = {Choosing the best model},
	url = {http://www.sciencedirect.com/science/article/pii/0895717796001033},
	doi = {10.1016/0895-7177(96)00103-3},
	abstract = {he lack of a methodology, or at least detailed guidelines, for choosing the best model in a mathematical or computer modelling study stems from a poor understanding of the precise ways in which the success of the study depends upon the particular model used. As a result, the choice of the best model is regarded as more of an art than a science. In order to improve the model selection process, model performance needs to be clearly defined, and suitable model attributes identified that can be used to predict the performance of the alternative candidate models. This paper distinguishes the different aspects of model performance and considers the extent to which they can be measured. The most common attributes used to compare alternative models are level of detail and complexity although these terms are used in a number of different ways. The meanings of these concepts are therefore discussed and the likely relationships with the model performance elements considered. The related area of simplification is reviewed and the areas in which further work is required are set out.},
	number = {4},
	urldate = {2014-08-12},
	journal = {Mathematical and Computer Modelling},
	author = {Brooks, R. J. and Tobias, A. M.},
	month = aug,
	year = {1996},
	pages = {1--14},
	file = {Brooks.Tobias.1996.ChoosingTheBestModel.PDF:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Brooks.Tobias.1996.ChoosingTheBestModel.PDF:application/pdf}
}

@book{thagard_coherence_2002,
	title = {Coherence in {Thought} and {Action}},
	isbn = {978-0-262-70092-4},
	abstract = {This book is an essay on how people make sense of each other and the world they livein. Making sense is the activity of fitting something puzzling into a coherent pattern of mentalrepresentations that include concepts, beliefs, goals, and actions. Paul Thagard proposes a generaltheory of coherence as the satisfaction of multiple interacting constraints, and discusses thetheory's numerous psychological and philosophical applications. Much of human cognition can beunderstood in terms of coherence as constraint satisfaction, and many of the central problems ofphilosophy can be given coherence-based solutions. Thagard shows how coherence can help to unifypsychology and philosophy, particularly when addressing questions of epistemology, metaphysics,ethics, politics, and aesthetics. He also shows how coherence can integrate cognition andemotion.},
	language = {en},
	publisher = {MIT Press},
	author = {Thagard, Paul},
	year = {2002},
	keywords = {vveitas:cognitive\_development},
	file = {Thagard.2000.CoherenceInThoughtAndAction.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Thagard.2000.CoherenceInThoughtAndAction.pdf:application/pdf}
}

@book{boden_mind_2006,
	title = {Mind as {Machine}: {A} {History} of {Cognitive} {Science}},
	isbn = {978-0-19-954316-8},
	shorttitle = {Mind as {Machine}},
	language = {en},
	publisher = {Oxford University Press},
	author = {Boden, Margaret A.},
	year = {2006},
	file = {Boden.2006.MindAsMachine.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Boden.2006.MindAsMachine.pdf:application/pdf}
}

@misc{melbourne_learning_nodate,
	title = {Learning experience: let's take consciousness in from the cold},
	shorttitle = {Learning experience},
	url = {http://theconversation.com/learning-experience-lets-take-consciousness-in-from-the-cold-6739},
	abstract = {Until 20 years ago, scientists interested in empirical work on consciousness – our private subjective experiences – hid it by minimising or eliminating the “c-word”, the use of which was a career-limiting…},
	urldate = {2014-08-12},
	journal = {The Conversation},
	author = {Melbourne, Colin Hales Researcher in brain electrodynamics at the Centre for Neural Engineering at University of},
	file = {Halles.2012.LearningExperienceLetsTakeConsciousnessInFromTheCold.BlogPost.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Halles.2012.LearningExperienceLetsTakeConsciousnessInFromTheCold.BlogPost.pdf:application/pdf}
}

@article{bhak_atom_2004,
	title = {The {Atom} of {Evolution}},
	volume = {2},
	issn = {1598-866X},
	abstract = {The main mechanism of evolution is that biological entities change, are selected, and reproduce. We propose a different concept in terms of the main agent or atom of evolution: in the biological world, not an individual object, but its interactive network is the fundamental unit of evolution. The interaction network is composed of interaction pairs of information objects that have order information. This indicates a paradigm shift from 3D biological objects to an abstract network of information entities as the primary agent of evolution. It forces us to change our views about how organisms evolve and therefore the methods we use to analyze evolution.},
	number = {4},
	journal = {Genomics \& Informatics},
	author = {Bhak, Jonghwa and Bolser, Dan},
	year = {2004},
	file = {Bhak.Bolster.2004.TheAtomOfEvolution.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Bhak.Bolster.2004.TheAtomOfEvolution.pdf:application/pdf}
}

@book{perls_gestalt_1992,
	title = {Gestalt {Therapy} {Verbatim}},
	isbn = {978-0-939266-16-6},
	language = {en},
	publisher = {Gestalt Journal Press},
	author = {Perls, Frederick S.},
	year = {1992},
	keywords = {vveitas:cognitive\_development},
	file = {Perls.1992.GestaltTheoryVerbatim.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Perls.1992.GestaltTheoryVerbatim.pdf:application/pdf}
}

@book{cooper_essential_2008,
	title = {Essential {Research} {Findings} in {Counselling} and {Psychotherapy}: {The} {Facts} are {Friendly}},
	isbn = {978-1-4462-4265-0},
	shorttitle = {Essential {Research} {Findings} in {Counselling} and {Psychotherapy}},
	abstract = {Are some therapies more effective than others? How important is the relationship? Which clients do best in therapy?   Essential Research Findings in Counselling and Psychotherapy answers these questions and many more, providing trainees, practitioners and researchers with a comprehensive introduction to the latest findings in the field. The book sets out in a jargon-free way the evidence for the effectiveness of therapy and the factors associated with positive therapeutic outcomes. It gives suggestions for further reading, definitions of key terms and questions for discussion, making this an ideal text for use in training.   The book is also designed for practitioners who increasingly need to justify their therapeutic work on empirical grounds. Essential Research Findings in Counselling and Psychotherapy gives them the knowledge and confidence to do just that. More than that, it makes research findings accessible and provides information on how to practice counselling and psychotherapy in an effective way.   Watch Mick Cooper talking about this book on YouTube:  To view the Part 1 - Click Here To view the Part 2 - Click Here To view the Part 3 - Click Here},
	language = {en},
	publisher = {SAGE},
	author = {Cooper, Mick},
	month = sep,
	year = {2008},
	file = {Cooper.2008.EssentialResearchFindingsInCouncellingAndPsychotherapy.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Cooper.2008.EssentialResearchFindingsInCouncellingAndPsychotherapy.pdf:application/pdf}
}

@incollection{heylighen_self-organization_2013,
	series = {Understanding {Complex} {Systems}},
	title = {Self-organization in {Communicating} {Groups}: {The} {Emergence} of {Coordination}, {Shared} {References} and {Collective} {Intelligence}},
	copyright = {©2013 Springer-Verlag Berlin Heidelberg},
	isbn = {978-3-642-32816-9 978-3-642-32817-6},
	shorttitle = {Self-organization in {Communicating} {Groups}},
	url = {http://link.springer.com/chapter/10.1007/978-3-642-32817-6_10},
	abstract = {Complex adaptive systems consist of a large number of interacting agents. Agents are goal-directed, cognitive individuals capable of perception, information processing and action. However, agents are intrinsically “bounded” in their rational understanding of the system they belong to, and its global organization tends to emerge from local interactions, resulting in a coordination of the agents and their actions. This coordination minimizes conflict or friction, while facilitating cooperation or synergy. The basic mechanism is the reinforcement of synergetic interactions and the suppression of conflictual ones. As a result, the system as a whole starts to behave like an integrated cognitive “superagent”. The author presents several examples of this process of spontaneous coordination that leads to distributed cognition, including the emergence of a shared vocabulary, the development of standard referential expressions, the evolution of transmitted ideas (memes) towards more stereotypical forms, and the aggregation of diverse experiences into collective decisions, in which the system as a whole is more intelligent than its individual components. These phenomena have been investigated by means of multi-agent computer simulations and social psychological experiments.},
	language = {en},
	urldate = {2014-08-11},
	booktitle = {Complexity {Perspectives} on {Language}, {Communication} and {Society}},
	publisher = {Springer Berlin Heidelberg},
	author = {Heylighen, Francis},
	editor = {Massip-Bonet, Àngels and Bastardas-Boada, Albert},
	month = jan,
	year = {2013},
	keywords = {vveitas:cognitive\_development},
	pages = {117--149},
	file = {Heylighen.2013.SellfOrganizationInCommunicationgGroups.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Heylighen.2013.SellfOrganizationInCommunicationgGroups.pdf:application/pdf}
}

@misc{noauthor_sensemaking_2014,
	title = {Sensemaking},
	copyright = {Creative Commons Attribution-ShareAlike License},
	url = {http://en.wikipedia.org/w/index.php?title=Sensemaking&oldid=615797729},
	abstract = {Sensemaking is the process by which people give meaning to experience. While this process has been studied by other disciplines under other names for centuries, the term "sensemaking" has primarily marked three distinct but related research areas since the 1970s: Sensemaking was introduced to Human–computer interaction by PARC researchers Russell, Stefik, Pirolli and Card in 1993, to information science by Brenda Dervin, and organizational studies by Karl Weick.},
	language = {en},
	urldate = {2014-08-11},
	journal = {Wikipedia, the free encyclopedia},
	month = aug,
	year = {2014},
	note = {Page Version ID: 615797729},
	file = {Snapshot:/home/kabir/Zotero/storage/ZUBCEH99/index.html:text/html}
}

@book{noauthor_artificial_nodate,
	title = {Artificial {General} {Intelligence} - 7th {International} {Conference}, {AGI} 2014, {Quebec} {City}, {QC}, {Canada},},
	url = {http://www.springer.com/computer/ai/book/978-3-319-09273-7},
	abstract = {This book constitutes the refereed proceedings of the 7th International Conference on Artificial General Intelligence, AGI 2014, held in Quebec City, QC, Canada, in August 2014. The 22 papers and 8 posters were carefully reviewed ...},
	urldate = {2014-08-11},
	file = {Goertzel.EtAl(Eds).2014.ArtificialGeneralIntelligenceAGI14ConferenceProceedings.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Goertzel.EtAl(Eds).2014.ArtificialGeneralIntelligenceAGI14ConferenceProceedings.pdf:application/pdf}
}

@book{combes_gilbert_2013,
	title = {Gilbert {Simondon} and the {Philosophy} of the {Transindividual}},
	isbn = {978-0-262-01818-0},
	abstract = {Gilbert Simondon (1924--1989), one of the most influential contemporary Frenchphilosophers, published only three works: L'individu et sa genèse physico-biologique(The individual and its physico-biological genesis, 1964) and  L'individuationpsychique et collective (Psychic and collective individuation, 1989), both drawn from hisdoctoral thesis, and Du mode d'existence des objets techniques (On the mode ofexistence of technical objects, 1958). It is this last work that brought Simondon into the publiceye; as a consequence, he has been considered a "thinker of technics" and cited often inpedagogical reports on teaching technology. Yet Simondon was a philosopher whose ambitions lay in anin-depth renewal of ontology as a process of individuation--that is, how individuals come intobeing, persist, and transform. In this accessible yet rigorous introduction to Simondon's work,Muriel Combes helps to bridge the gap between Simondon's account of technics and his philosophy ofindividuation. Some thinkers have found inspiration in Simondon's philosophy of individuation,notably Gilles Deleuze and Félix Guattari. Combes's account, first published in French in 1999, isone of the only studies of Simondon to appear in English. Combes breaks new ground, exploring anethics and politics adequate to Simondon's hypothesis of preindividual being, considering throughthe lens of transindividual philosophy what form a nonservile relation to technology might taketoday. Her book is essential reading for anyone who wants to understand Simondon's work.},
	language = {en},
	publisher = {MIT Press},
	author = {Combes, Muriel},
	year = {2013},
	keywords = {vveitas:cognitive\_development, vveitas:vienna2015},
	file = {Combes.2013.GilbertSimondonAndThePhilosophyOfTheTransindividual.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Combes.2013.GilbertSimondonAndThePhilosophyOfTheTransindividual.pdf:application/pdf}
}

@article{baars_global_2013,
	title = {Global {Workspace} {Dynamics}: {Cortical} "{Binding} and {Propagation}" {Enables} {Conscious} {Contents}},
	volume = {4},
	issn = {1664-1078},
	shorttitle = {Global {Workspace} {Dynamics}},
	url = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3664777/},
	doi = {10.3389/fpsyg.2013.00200},
	abstract = {A global workspace (GW) is a functional hub of binding and propagation in a population of loosely coupled signaling elements. In computational applications, GW architectures recruit many distributed, specialized agents to cooperate in resolving focal ambiguities. In the brain, conscious experiences may reflect a GW function. For animals, the natural world is full of unpredictable dangers and opportunities, suggesting a general adaptive pressure for brains to resolve focal ambiguities quickly and accurately. GW theory aims to understand the differences between conscious and unconscious brain events. In humans and related species the cortico-thalamic (C-T) core is believed to underlie conscious aspects of perception, thinking, learning, feelings of knowing (FOK), felt emotions, visual imagery, working memory, and executive control. Alternative theoretical perspectives are also discussed. The C-T core has many anatomical hubs, but conscious percepts are unitary and internally consistent at any given moment. Over time, conscious contents constitute a very large, open set. This suggests that a brain-based GW capacity cannot be localized in a single anatomical hub. Rather, it should be sought in a functional hub – a dynamic capacity for binding and propagation of neural signals over multiple task-related networks, a kind of neuronal cloud computing. In this view, conscious contents can arise in any region of the C-T core when multiple input streams settle on a winner-take-all equilibrium. The resulting conscious gestalt may ignite an any-to-many broadcast, lasting ∼100–200 ms, and trigger widespread adaptation in previously established networks. To account for the great range of conscious contents over time, the theory suggests an open repertoire of binding1 coalitions that can broadcast via theta/gamma or alpha/gamma phase coupling, like radio channels competing for a narrow frequency band. Conscious moments are thought to hold only 1–4 unrelated items; this small focal capacity may be the biological price to pay for global access. Visuotopic maps in cortex specialize in features like color, retinal size, motion, object identity, and egocentric/allocentric framing, so that a binding coalition for the sight of a rolling billiard ball in nearby space may resonate among activity maps of LGN, V1-V4, MT, IT, as well as the dorsal stream. Spatiotopic activity maps can bind into coherent gestalts using adaptive resonance (reentry). Single neurons can join a dominant coalition by phase tuning to regional oscillations in the 4–12 Hz range. Sensory percepts may bind and broadcast from posterior cortex, while non-sensory FOKs may involve prefrontal and frontotemporal areas. The anatomy and physiology of the hippocampal complex suggest a GW architecture as well. In the intact brain the hippocampal complex may support conscious event organization as well as episodic memory storage.},
	urldate = {2014-08-02},
	journal = {Frontiers in Psychology},
	author = {Baars, Bernard J. and Franklin, Stan and Ramsoy, Thomas Zoega},
	month = may,
	year = {2013},
	pmid = {23974723},
	pmcid = {PMC3664777},
	file = {Baars.EtAl.2013.GlobalWorkspaceDynamics.pdf:/media/vveitas/LibraryKing/gdrive/vveitas@gmail.com/library/Baars.EtAl.2013.GlobalWorkspaceDynamics.pdf:application/pdf}
}

@article{bengio_how_2014,
	title = {How {Auto}-{Encoders} {Could} {Provide} {Credit} {Assignment} in {Deep} {Networks} via {Target} {Propagation}},
	url = {http://arxiv.org/abs/1407.7906},
	abstract = {In this paper we propose to exploit \{{\textbackslash}em reconstruction\} as a layer-local training signal for deep learning, be it generative or discriminant, single or multi-modal, supervised, semi-supervised or unsupervised, feedforward or recurrent. Reconstructions can be propagated in a form of target propagation playing a role similar to back-propagation but helping to reduce the reliance on back-propagation in order to perform credit assignment across many levels of possibly strong non-linearities (which is difficult for back-propagation). A regularized auto-encoder tends produce a reconstruction that is a more likely version of its input, i.e., a small move in the direction of higher likelihood. By generalizing gradients, target propagation may also allow to train deep networks with discrete hidden units. If the auto-encoder takes both a representation of input and target (or of any side information) in input, then its reconstruction of input representation provides a target towards a representation that is more likely, conditioned on all the side information. A deep auto-encoder decoding path generalizes gradient propagation in a learned way that can thus handle not just infinitesimal changes but larger, discrete changes, hopefully allowing credit assignment through a long chain of non-linear operations. For this to work, each layer must be a good denoising or regularized auto-encoder itself. In addition to each layer being a good auto-encoder, the encoder also learns to please the upper layers by transforming the data into a space where it is easier to model by them, flattening manifolds and disentangling factors. The motivations and theoretical justifications for this approach are laid down in this paper, along with conjectures that will have to be verified either mathematically or experimentally.},
	urldate = {2014-08-02},
	journal = {arXiv:1407.7906 [cs]},
	author = {Bengio, Yoshua},
	month = jul,
	year = {2014},
	note = {arXiv: 1407.7906},
	file = {Bengio.2014.HowAutoEncodersCouldProvideCreditAssignmentInDeepNetowkrsViaTargetPropagation.pdf:/media/vveitas/LibraryKing/gdrive/vveitas@gmail.com/library/Bengio.2014.HowAutoEncodersCouldProvideCreditAssignmentInDeepNetowkrsViaTargetPropagation.pdf:application/pdf}
}

@article{fodor_connectionism_1988,
	title = {Connectionism and cognitive architecture: {A} critical analysis},
	volume = {28},
	issn = {0010-0277},
	url = {http://www.sciencedirect.com/science/article/pii/0010027788900315},
	doi = {10.1016/0010-0277(88)90031-5},
	number = {1–2},
	journal = {Cognition},
	author = {Fodor, Jerry A. and Pylyshyn, Zenon W.},
	year = {1988},
	pages = {3--71},
	file = {Fodor.Pylishin.1988.ConectinismAndCognitiveArchitecture.pdf:/media/data/vveitas/gdrive/vveitas@gmail.com/library/Fodor.Pylishin.1988.ConectinismAndCognitiveArchitecture.pdf:application/pdf}
}

@article{kaplan_who_2004,
	title = {Who is afraid of the humanoid? {Investigating} cultural differences in the acceptance of robots},
	volume = {2004},
	shorttitle = {Who is afraid of the humanoid?},
	abstract = {Are robots perceived in the same manner in the West and in Japan? This article presents a preliminary exploration of several aspects of the Japanese culture and a survey of the most important myths and novels involving artificial beings in Western literature. Through this analysis, the article tries to shed light on particular cultural features that may account for contemporary differences in our behavior towards humanoids.},
	journal = {International Journal of Humanoid Robotics},
	author = {Kaplan, Frédéric},
	year = {2004},
	pages = {1--16},
	file = {Kaplan.2010.WhoIsAfraidOfTheHumanoidInvestigatingCulturalDifferencesInTheAcceptionOfRobots.pdf:/media/vveitas/LibraryKing/gdrive/vveitas@gmail.com/library/Kaplan.2010.WhoIsAfraidOfTheHumanoidInvestigatingCulturalDifferencesInTheAcceptionOfRobots.pdf:application/pdf}
}

@book{picard_learning_2010

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repo_name: singnet/offernet

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