AI RESEARCH
Influencing LLM Multi-Agent Dialogue via Policy-Parameterized Prompts
arXiv CS.AI
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ArXi:2603.09890v1 Announce Type: new Large Language Models (LLMs) have emerged as a new paradigm for multi-agent systems. However, existing research on the behaviour of LLM-based multi-agents relies on ad hoc prompts and lacks a principled policy perspective. Different from reinforcement learning, we investigate whether prompt-as-action can be parameterized so as to construct a lightweight policy which consists of a sequence of state-action pairs to influence conversational behaviours without