Distributed problem solving and planning
Multiagent systems
Effects of Individual Decision Schemes on Group Behavior
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
Adaptive load balancing: a study in multi-agent learning
Journal of Artificial Intelligence Research
Developing Alternative Mechanisms for Multiagent Coordination
Proceedings of the 5th Pacific Rim International Workshop on Multi Agents: Intelligent Agents and Multi-Agent Systems
Norms for DLP Agents Working in a Warehouse Scenario
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
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A decentralized multiagent system comprises agents who act autonomously based on local knowledge. Achieving coordination in such a system is nontrivial, hut is essential in most applications, where disjointed or incoherent behavior would be undesirable. Coordination in decentralized systems is a richer phenomenon than previously believed. In particular, five major attributes are crucial: the extent of the local knowledge and choices of the member agents, the extent of their shared knowledge, the level of their inertia, and the level of precision of the required coordination. Interestingly, precision and inertia turn out to control the coordination process. They define different regions within each of which the other attributes relate nicely with coordination, but among which their relationships are altered or even reversed. Based on our study, we propose simple design rules to obtain coordinated behavior in decentralized multiagent systems.