Using Answer Set Programming to Model Multi-Agent Scenarios Involving Agents' Knowledge About Other's Knowledge
One of the most challenging aspects of reasoning, planning, and acting in a multi-agent domain is reasoning about what the agents know about the knowledge of their fellows, and to take it into account when planning and acting. In the past this has been done using modal and dynamic epistemic logics. In this paper, the authors explore the use of Answer Set Programming (ASP), and reasoning about action techniques for this purpose. These approaches present a number of theoretical and practical advantages. From the theoretical perspective, ASP's property of non-monotonicity (and several other features) allow one to express causality in an elegant fashion. From the practical perspective, recent implementations of ASP solvers have become very efficient, outperforming several other systems in recent SAT competitions.