The existing reinforcement learning approaches have been suffering from the policy alternation of others in multiagent dynamic environments such as RoboCup competitions since othe...
In this paper we describe a channel-based exogenous coordination language, called Reo, and discuss its application to multi-agent systems. Reo supports a specific notion of compo...
In this paper, we focus on the coordination issues in a multiagent setting. Two coordination algorithms based on reinforcement learning are presented and theoretically analyzed. O...
Achieving effective cooperation in a multi-agent system is a difficult problem for a number of reasons such as limited and possiblyout-datedviews of activitiesof other agents and ...
This paper presents a novel method for on-line coordination in multiagent reinforcement learning systems. In this method a reinforcement-learning agent learns to select its action ...