Evaluating Theory of Mind and Internal Beliefs in LLM-Based Multi-Agent Systems
- Published
- Source
- arXiv
- Paper number
- 124
- Field
- Multi-Agent
- arXiv ID
- 2603.00142
Key points
- LLM agents often show inconsistent and variable performance in complex multi-agent systems, especially when dealing with partial or conflicting information.
- Existing multi-agent systems often rely on rigid rules, which limits their adaptability and scalability in dynamic real-world environments.
- A comprehensive, synergistically integrated structure that combines theory of mind (ToM), internal belief systems, and logical verification is still missing from LLM-based multi-agent systems.
- We propose a new agent architecture that integrates theory of mind (ToM) capability, internal belief states (IB), and logical verification using an answer set programming (ASP) solver.
- We deployed these agents in an interactive city resource allocation simulation designed to require effective coordination under dynamic, resource-consuming scenarios.
- The modular agent design enabled systematic evaluation of four configurations, baseline, ToM only, IB only, and ToM plus IB, across different LLMs, with iterative logical consistency checks on internal beliefs.
Paper links
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