---
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
1. **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.
2. **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.
3. **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`