Can shared memory improve AI team foraging?
HIGH-FIDELITY SOCIAL LEARNING VIA SHARED EPISODIC MEMORIES ENHANCES COLLABORATIVE FORAGING THROUGH ΜΝΕΜΟΝIC CONVERGENCE
This research investigates how sharing memories helps AI agents learn to collaborate better in a foraging task. They use a brain-inspired AI model called Sequential Episodic Control (SEC) where agents remember successful action sequences and can share them with others.
The key takeaway for LLM-based multi-agent systems is that high-fidelity memory sharing (accurate information transfer) significantly boosts collaborative performance. Sharing frequently is beneficial, but only if the information is accurate. Inaccurate sharing ("low-fidelity") actually hinders learning. This suggests that careful control of information quality during LLM agent communication is crucial for effective collaboration. Also, the work indicates that the size of the memory buffer containing previous successful action sequences can constrain agent learning.