EFP 2.0: A Multi-Agent Epistemic Solver with Multiple E-State Representations

Abstract

Multi-agent systems have been employed to model, simulate and explore a variety of real-world scenarios. It is becoming more and more important to investigate formalisms and tools that would allow us to exploit automated reasoning in these domains. An area that has received increasing attention is the use of multi-agent systems which allow an agent to reason about the knowledge and beliefs of other agents. This type of reasoning, i.e., about agents' perception of the world and also about agents' knowledge of her and others' knowledge, is referred to as epistemic reasoning. This paper presents an updated formalization and implementation of a multi-agent epistemic planner, called EFP. In particular, the paper explores the advantages of using alternative state representations that deviate from the commonly used Kripke structures. The paper explores such alternatives in the context of an action language for multi-agent epistemic planning. The paper presents also an actual implementation of a planner that uses the novel ideas, demonstrating concrete performance improvements on benchmarks collected from the literature.