Multi-Agent Coordination: A Reinforcement Learning Approach

by Amit Konar and Arup Kumar Sadhu

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This book explores the usage of Reinforcement Learning for Multi-Agent Coordination. Chapter 1 introduces fundamentals of the multi-robot coordination. Chapter 2 offers two useful properties, which have been developed to speed-up the convergence of traditional multi-agent Q-learning (MAQL) algorithms in view of the team-goal exploration, where team-goal exploration refers to simultaneous exploration of individual goals. Chapter 3 proposes the novel...

Format:Hardcover

Language:English

ISBN:1119699037

ISBN13:9781119699033

Release Date:December 2020

Publisher:Wiley-IEEE Press

Length:320 Pages

Weight:1.31 lbs.

Dimensions:0.8" x 6.0" x 9.0"

Related Subjects

Computers Computers & Technology

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Multi-Agent Coordination: A Reinforcement Learning Approach

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