Reasoning about the Beliefs of Agents in Multi-agent Domains in the Presence of State Constraints: The Action Language mAL

Abstract

Reasoning about actions forms the basis of many tasks such as prediction, planning, and diagnosis in a dynamic domain. Within the reasoning about actions community, a broad class of languages called action languages has been developed together with a methodology for their use in representing dynamic domains. With a few notable exceptions, the focus of these efforts has largely centered around single-agent systems. Agents rarely operate in a vacuum however, and almost in parallel, substantial work has been done within the dynamic epistemic logic community towards understanding how the actions of an agent may affect the knowledge and/or beliefs of his fellows. What is less understood by both communities is how to represent and reason about both the direct and indirect effects of both ontic and epistemic actions within a multi-agent setting. This paper presents a new action language, m $\mathcal{AL}$, which brings together techniques developed in both communities for reasoning about dynamic multi-agent domains involving both ontic and epistemic actions, as well as the indirect effects that such actions may have on the domain.