Individual Planning in Open and Typed Agent Systems

Abstract

Open agent systems are multiagent systems in which one or more agents may leave the system at any time possibly resuming after some interval and in which new agents may also join. Planning in such systems becomes challenging in the absence of inter-agent communication because agents must predict if others have left the system or new agents are now present to decide on possibly choosing a different line of action. In this paper, we prioritize open systems where agents of differing types may leave and possibly reenter but new agents do not join. With the help of a realistic domain -- wildfire suppression -- we motivate the need for individual planning in open environments and present a first approach for robust decision-theoretic planning in such multiagent systems. Evaluations in domain simulations clearly demonstrate the improved performance compared to previous methods that disregard the openness.