Datasets:
title: 'House Oversight: Estate Documents (Nov 12) (HOUSE_OVERSIGHT_012971)'
source: 'House Oversight: Estate Documents (Nov 12)'
sourceUrl: https://www.justice.gov/epstein
date: '2026-01-01'
category: House Oversight
eftaNumber: HOUSE_OVERSIGHT_012971
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3.6 Postscript: Formalizing Pattern 55 Using this definition of pattern, combined with the formal theory of intelligence given in Chapter 7, one may formalize the various hypotheses made in the previous section, regarding the emergence of different kinds of networks and structures as patterns in intelligent systems. However, it appears quite difficult to prove the formal versions of these hypotheses given current mathematical tools, which renders such formalizations of limited use. Finally, consider the case where the metric space M has a partial ordering < on it; we may Definition 3.1. R. € M is a subpattern in X € M to the degree K- JDEM true(R< P)dig JPEM diX This degree is called the subpattern intensity of P in X. Roughly speaking, the subpattern intensity measures the percentage of patterns in X that contain R (where "containment" is judged by the partial ordering <). But the percentage is measured using a weighted average, where each pattern is weighted by its intensity as a pattern in X. A subpattern may or may not be a pattern on its own. A nonpattern that happens to occur within many patterns may be an intense subpattern. Whether the subpatterns in X are to be considered part of the "mind" of X is a somewhat superfluous question of semantics. Here we choose to extend the definition of mind given in Goe06a to include subpatterns as well as patterns, because this makes it simpler to describe the relationship between hypersets and minds, as we will do in Appendix ??. HOUSE_OVERSIGHT_012971