How can I make LLMs cooperate better?
Identifying Cooperative Personalities in Multi-agent Contexts through Personality Steering with Representation Engineering
This research explores how personality traits influence cooperation in Large Language Models (LLMs) within a multi-agent game setting (Iterated Prisoner's Dilemma). By steering LLM personalities using representation engineering to embody traits like agreeableness and conscientiousness, researchers observed increased cooperation. However, this also made the LLMs more susceptible to exploitation by other agents. Key points include: personality affects LLM behavior in multi-agent scenarios; some traits improve cooperation but increase vulnerability; steering LLM personality through representation engineering is possible and affects outcomes in interactions; communication between agents influences behavior and exploitability; and overall, balancing cooperation and robustness against exploitation is crucial in LLM-based multi-agent system design.