Efficient Multiagent Coordination in Dynamic Environments

Agent coordination is a fundamental task in designing and operating multiagent systems. However, in dynamically changing environments, coordination must balance proactive and reactive behaviors in order to enable efficient operations while retaining the necessary flexibility to react to unforeseen events. This paper introduces adaptive agent relationships for coping with these contradictory requirements. In this approach, agents dynamically establish relationships which are represented as interaction patterns. On the one hand, these patterns enable efficient coordination by restricting the number of potential interaction flows to those offering the best estimated outcome. On the other hand, they can adapt to environmental changes, as the agents continuously reconsider their relationships in a feedback loop of estimated interaction flows and actually observed coordination outcomes. The paper formalizes the agent decision-making process enabling adaptive relationships and applies it to a logistics network scenario. A comparative evaluation demonstrates its ability to efficiently coordinate agent interaction in a dynamic environment.