Title: A General Multi-agent Epistemic Planner Based on Higher-order Belief Change

Presented By: Yongmei Liu, Sun Yat-sen University

Abstract:

In recent years, multi-agent epistemic planning has received attention from both dynamic logic and planning communities. Existing implementations of multi-agent epistemic planning are based on compilation into classical planning and suffer from various limitations, such as generating only linear plans, restriction to public actions, and incapability to handle disjunctive beliefs. In this talk, I will introduce our work on a multi-agent epistemic planning framework based on higher-order belief change. In our framework, the initial KB and the goal, the preconditions and effects of actions can be arbitrary multi-agent epistemic formulas, and the solution is an action tree branching on sensing results. To support efficient reasoning in the multi-agent KD45 logic, we make use of a normal form called alternating cover disjunctive formulas (ACDFs). We propose reasoning and basic revision and update algorithms for ACDFs. Based on our reasoning, revision and update algorithms, adapting the PrAO algorithm for contingent planning from the literature, we implemented a multi-agent epistemic planner called MEPK. Our experimental results show the viability of our approach. We have also extended our framework with the capability to deal with common knowledge.

Biography:

Yongmei Liu is a Professor of Computer Science at Sun Yat-sen University, China. She received her PhD in Computer Science from the University of Toronto. Her research interests are in knowledge representation and reasoning in Artificial Intelligence, reasoning about actions, cognitive robotics, program verification and synthesis.