Planning in Multi-Agent Domains with Untruthful Announcements

Abstract

Earlier epistemic planning systems for multi-agent domains generate plans that contain various types of actions such as ontic, sensing, or announcement actions. However, none of these systems consider untruthful announcements, i.e., none can generate plans that contain a lying or a misleading announcement. In this paper, we present a novel epistemic planner, called EFP3.0, for multi-agent domains with untruthful announcements. The planner is similar to the systems EFP or EFP2.0 in that it is a forward-search planner and can deal with unlimited nested beliefs and common knowledge by employing a Kripke based state representation and implementing an update model based transition function. Different from EFP, EFP3.0 employs a specification language that uses edge-conditioned update models for reasoning about effects of actions in multi-agent domains. We describe the basics of EFP3.0 and conduct experimental evaluations of the system against state-of-the-art epistemic planners. We discuss potential improvements that could be useful for scalability and efficiency of the system.