metadata
title: Adaptive Agent Memory Resilience Playground
colorFrom: indigo
colorTo: blue
sdk: static
pinned: true
license: apache-2.0
short_description: Bayesian Trust Engine & Pessimistic LCB Retrieval
Adaptive Agent Memory Resilience Playground
An interactive research playground demonstrating mathematical trust dynamics and pessimistic memory retrieval for autonomous LLM agents (LangGraph, AutoGen, CrewAI).
This Space accompanies the research paper: "Adaptive Agent Memory Resilience: Mitigating Negative Transfer and Memory Poisoning via Bayesian Trust Updating and Pessimistic Lower Confidence Bound Retrieval" by Sumit Das (2026).
Live Demonstrations
- Bayesian Reliability & Statistical Quarantine:
- Conjugate Beta-Bernoulli updating ($\alpha_0=3.0, \beta_0=1.0$).
- Dynamic epistemic uncertainty estimation ($\sigma = \sqrt{\operatorname{Var}[\theta]}$).
- Incomplete Beta integral for reliability threshold $\mathbb{P}(\theta > 0.70)$.
- Theorem 1 deterministic quarantine trigger at $t^* = 4$ consecutive failures.
- Pessimistic LCB Memory Retriever:
- Compare unweighted Cosine Similarity against the proposed composite Lower Confidence Bound ($\operatorname{LCB}_\lambda$) ranking: $\operatorname{Score}(e; q) = \operatorname{Sim}(\mathbf{q}, \mathbf{v}_e) \times \operatorname{LCB}_\lambda(e)$
- Demonstrates suppression of corrupted high-similarity strategies under adversarial drift.
- Empirical Benchmark Explorer:
- Live inspection of 1,200 execution traces and 100 experiential memories comparing 4 experimental ablation conditions.
Dataset Reference
The full benchmark dataset is available at:
sumitaidev/agent-memory-resilience-benchmark