Game−Theoretic Agent Programming in Golog

Abstract

We present the agent programming language GTGolog, which integrates explicit agent programming in Golog with game-theoretic multi-agent planning in Markov games. It is a generalization of DTGolog to a multi-agent setting, where we have two competing single agents or two competing teams of agents. The language allows for specifying a control program for a single agent or a team of agents in a high-level logical language. The control program is then completed by an interpreter in an optimal way against another single agent or another team of agents, by viewing it as a generalization of a Markov game, and computing a Nash strategy. We illustrate the usefulness of this approach along a robotic soccer example.