How memory can affect collective and cooperative behaviors in an LLM-Based Social Particle Swarm
This study examines how memory shapes the collective and cooperative dynamics of Large Language Model (LLM) agents in a multi-agent system. To this end, we extend the Social Particle Swarm (SPS) model, in which agents move in a two-dimensional space and play the Prisoner's Dilemma with neighboring agents, by replacing its rule-based agents with LLM agents endowed with Big Five personality scores and varying memory lengths. Using Gemini 2.0 Flash, we find that memory length is a critical parameter governing collective behavior: even a minimal memory drastically suppressed cooperation, transitioning the system from stable cooperative clusters through cyclical formation and collapse of clust...
| Authors | Taisei Hishiki, Takaya Arita, Reiji Suzuki |
|---|---|
| Primary category | cs.AI |
| Published | 14 April 2026 |
| Last updated at source | 29 July 2026 |
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