Planning Over Multi-Agent Epistemic States: A Classical Planning Approach


  • Christian Muise University of Melbourne
  • Vaishak Belle University of Toronto
  • Paolo Felli University of Melbourne
  • Sheila McIlraith University of Toronto
  • Tim Miller University of Melbourne
  • Adrian Pearce University of Melbourne
  • Liz Sonenberg University of Melbourne



planning, epistemic reasoning, multi-agent, nested belief


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. Our approach represents an important first step towards applying the well-established field of automated planning to the challenging task of planning involving nested beliefs of multiple agents.




How to Cite

Muise, C., Belle, V., Felli, P., McIlraith, S., Miller, T., Pearce, A., & Sonenberg, L. (2015). Planning Over Multi-Agent Epistemic States: A Classical Planning Approach. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1).