EPMC Gets Knowledge in Multi-agent Systems

Chen Fu, Ernst Moritz Hahn, Yong Li, Sven Schewe, Meng Sun, Andrea Turrini, Lijun Zhang

Abstract: In this paper, we present EPMC, an extendible probabilistic model checker. EPMC has a small kernel, and is designed modularly. It supports discrete probabilistic models such as Markov chains and Markov decision processes. Like PRISM, it supports properties specified in PCTL*. Two central advantages of EPMC are its modularity and extendibility. We demonstrate these features by extending EPMC to EPMC-petl, a model checker for probabilistic epistemic properties on multi-agent systems. EPMC-petl takes advantage of EPMC to provide two model checking algorithms for multi-agent systems with respect to probabilistic epistemic logic: an exact algorithm based on SMT techniques and an approximated one based on UCT. Multi-agent systems and epistemic properties are given in an extension of the modelling language of PRISM, making it easy to model this kind of scenarios.