BeliefNest: A Joint Action Simulator for Embodied Agents with Theory of Mind
Embodied agents lack explicit Theory of Mind (ToM) modeling capabilities for open-domain collaborative tasks. Method: We propose BeliefNest, an open-source joint-action simulator built in Minecraft, featuring the first dynamic hierarchical nested belief modeling framework. It structurally represents self- and other-centered multi-order belief states as parseable graph models, directly mapped to LLM prompts to enable interpretable, evaluable ToM-driven decision-making. The approach integrates embodied simulation, hierarchical belief graphs, LLM prompt engineering, and a novel false-belief task evaluation protocol. Contribution/Results: Experiments demonstrate that BeliefNest accurately infers others’ beliefs and predicts belief-guided behavior. Quantitative evaluation on standardized false-belief tasks confirms that nested belief modeling significantly enhances multi-agent coordination performance, establishing a new benchmark for interpretable, ToM-aware embodied AI.