PsychoAgent: An Affect-Sensitive Cognitive Architecture for Conflict-Aware Memory in LLM Agents
Making AI remember emotional weight, not just matching keywords
A new system for AI assistants splits memory into facts and emotions, then retrieves past information based on what matters psychologically—not just topical similarity. In three conflict scenarios, this approach recovered conflict-critical details 40% more often than systems that treat all memories equally, though human raters couldn't consistently tell the difference in final conversation quality.
AI assistants today retrieve information like search engines: if you mention a topic, they pull up matching facts. But humans retrieve memories shaped by unresolved conflicts and emotional weight—what still bothers us. This work demonstrates a mechanism for building AI that prioritizes emotionally significant past events, potentially creating assistants that navigate complex, sensitive situations with better context awareness and more natural conversation flow.