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Fine Tuning of Agent-Based Evolutionary Computing

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DeepMind - The Role of Multi-Agent Learning in Artificial Intelligence Research

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References Publications referenced by this paper. Niching methods for genetic algorithms Samir W. The applications described are mainly in the areas of unmanned aerial vehicles UAVs and unmanned ground vehicles UGVs. Throughout, the authors link basic theory to multi-agent cooperative control practice — illustrated within the context of highly-realistic scenarios of high-level missions — without losing site of the mathematical background needed to provide performance guarantees under general working conditions. Many of the problems and solutions considered involve combinations of both types of vehicles.

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  • Topics explored include target assignment, target tracking, consensus, stochastic game theory-based framework, event-triggered control, topology design and identification, coordination under uncertainty and coverage control. The use of multi-agent system technologies in both everyday commercial use and national defense is certain to increase tremendously in the years ahead, making this book a valuable resource for researchers, engineers, and applied mathematicians working in systems and controls, as well as advanced undergraduates and graduate students interested in those areas.

    Her research interests include cooperative control and decision-making for multi-agent systems and human-robot interaction. Permissions Request permission to reuse content from this site. Quintero, David A.

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