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Game-Theoretic Learning and Distributed Optimization in Memoryless Multi-Agent Systems

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This book presents new efficient methods for optimization in realistic large-scale, multi-agent systems. These methods do not require the agents to have the full information about the system, but instead allow them to make their local decisions based only on the local information, possibly obtained during communication with their local neighbors.

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This book presents new efficient methods for optimization in realistic large-scale, multi-agent systems. These methods do not require the agents to have the full information about the system, but instead allow them to make their local decisions based only on the local information, possibly obtained during communication with their local neighbors.

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Book Format

Hardcover, Softcover

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Book information

Edition
1st Edition
ISBN [Hardcover]
9783319654782
ISBN [Softcover]
9783319880396
Publisher
Springer
Year
2017
Pages
IX, 171 p.
Language
English
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