Using limited information to enhance group stability
International Journal of Human-Computer Studies - Evolution and learning in multiagent systems
Be Patient and Tolerate Imprecision: How Autonomous Agents can Coordinate Effectively
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
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We investigate an environment where self-interested agents have to find high-quality service resources. Agents have common knowledge about resources which are able to provide these services. The performance of resources is measured by the satisfaction obtained by agents using them. The performance of a resource depends on its intrinsic capability and its current load. We use a satisfying rather than an optimizing framework, where agents are content to receive service quality above a threshold. We introduce a formal framework to characterize the convergence of agents to a state where each agent is satisfied with the performance of the service it is currently using. We analyzed the convergence behavior of such a system and identified a mechanism to speed up convergence.