This dataset models memory poisoning in AI agent systems. It detects when memory pressure, weakened validation buffer, governance lag in review, and tight coupling through shared state cross the five-node cascade threshold into an unrecoverable memory poisoning cascade.
This dataset models a five-node cascade: four interacting instability drivers and one emergent cascade state.The fifth node represents the nonlinear transition from recoverable drift to systemic… See the full description on the dataset page:
https://huggingface.co/datasets/ClarusC64/ai-5node-mem-buf-lag-cpl-memory-poisoning-v0.1.
