# Efficient Multi-agent Epistemic Planning: Teaching Planners About Nested Belief

arXiv: https://arxiv.org/abs/2110.02480 · HTML: https://mlsanity.com/paper/2110.02480/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 62 references that are in the map.
- First posted on arXiv 6 Oct 2021.

## Builds on (most cited first, 5 of 5)

- [Compiling Uncertainty Away in Conformant Planning Problems with Bounded Width](https://mlsanity.com/paper/1401.3468/) (2014)
- [A General Multi-agent Epistemic Planner Based on Higher-order Belief Change](https://mlsanity.com/paper/1806.11298/) (2018)
- [Cooperative Epistemic Multi-Agent Planning for Implicit Coordination](https://mlsanity.com/paper/1703.02196/) (2017)
- [Prime Implicates and Prime Implicants: From Propositional to Modal Logic](https://mlsanity.com/paper/1401.3475/) (2014)
- [Replanning in Domains with Partial Information and Sensing Actions](https://mlsanity.com/paper/1401.6048/) (2014)

## Built on by (most cited first, 7 of 7)

- [Grounding Language about Belief in a Bayesian Theory-of-Mind](https://mlsanity.com/paper/2402.10416/) (2024)
- [On verifying expectations and observations of intelligent agents](https://mlsanity.com/paper/2205.00784/) (2022)
- [BeliefNest: A Joint Action Simulator for Embodied Agents with Theory of Mind](https://mlsanity.com/paper/2505.12321/) (2025)
- [Learnability with PAC Semantics for Multi-agent Beliefs](https://mlsanity.com/paper/2306.05490/) (2023)
- [Depth-Bounded Epistemic Planning](https://mlsanity.com/paper/2406.01139/) (2024)
- [Beyond Static Assumptions: the Predictive Justified Perspective Model for Epistemic Planning](https://mlsanity.com/paper/2412.07941/) (2024)
- [Where Common Knowledge Cannot Be Formed, Common Belief Can -- Planning with Multi-Agent Belief Using Group Justified Perspectives](https://mlsanity.com/paper/2412.07981/) (2024)

## Abstract (arXiv)

Many AI applications involve the interaction of multiple autonomous agents, requiring those agents to reason about their own beliefs, as well as those of other agents. However, planning involving nested beliefs is known to be computationally challenging. In this work, we address the task of synthesizing plans that necessitate reasoning about the beliefs of other agents. We plan from the perspective of a single agent with the potential for goals and actions that involve nested beliefs, non-homogeneous agents, co-present observations, and the ability for one agent to reason as if it were another. We formally characterize our notion of planning with nested belief, and subsequently demonstrate how to automatically convert such problems into problems that appeal to classical planning technology for solving efficiently. Our approach represents an important step towards applying the well-established field of automated planning to the challenging task of planning involving nested beliefs of multiple agents.