PsychoAgent: An Affect-Sensitive Cognitive Architecture for Conflict-Aware Memory in LLM Agents

PsychoAgent filters affective memories by semantic relevance, reranks them by salience, and combines them with factual memory through an executive controller. In **three conflict scenarios**, retrieval scored **0.933**, versus 0.500 and 0.667 for two baselines.

For memory systems where importance is not captured by similarity alone, test a second ranking signal after relevance filtering. Keeping factual and affective stores separate also makes the retrieval policy easier to inspect.

Five blinded raters assessed **27 outputs**. The full system led by **+0.22 SD** after within-rater standardization, but corrected pairwise differences were not statistically significant, and retrieval incurred a small semantic-similarity cost.