Autonomous Agents and Multiagent Systems (AAMAS), 2006. A Stochastic Language for Modelling Opponent Agents ABSTRACT

Abstract

There are numerous cases where a reasoning agent needs to reason about the behavior of an opponent agent. In this paper, we propose a hybrid probabilistic logic language within which we can express what actions an opponent may take in a given situation. We present the syntaxis and semantics of the language, and the concept of a Maximally Probable Course of Action