Multi-Agent Coordination

Lingua: inglese

Editore: John Wiley and Sons Inc, US, 2020

1119699037 / 9781119699033

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Discover the latest developments in multi-robot coordination techniques with this insightful and original resource Multi-Agent Coordination: A Reinforcement Learning Approach delivers a comprehensive, insightful, and unique treatment of the development of multi-robot coordination algorithms with minimal computational burden and reduced storage requirements when compared to traditional algorithms. The accomplished academics, engineers, and authors provide readers with both a high-level introduction to, and overview of, multi-robot coordination, and in-depth analyses of learning-based planning algorithms. You'll learn about how to accelerate the exploration of the team-goal and alternative approaches to speeding up the convergence of TMAQL by identifying the preferred joint action for the team. The authors also propose novel approaches to consensus Q-learning that address the equilibrium selection problem and a new way of evaluating the threshold value for uniting empires without imposing any significant computation overhead. Finally, the book concludes with an examination of the likely direction of future research in this rapidly developing field. Readers will discover cutting-edge techniques for multi-agent coordination, including: An introduction to multi-agent coordination by reinforcement learning and evolutionary algorithms, including topics like the Nash equilibrium and correlated equilibriumImproving convergence speed of multi-agent Q-learning for cooperative task planningConsensus Q-learning for multi-agent cooperative planningThe efficient computing of correlated equilibrium for cooperative q-learning based multi-agent planningA modified imperialist competitive algorithm for multi-agent stick-carrying applications Perfect for academics, engineers, and professionals who regularly work with multi-agent learning algorithms, Multi-Agent Coordination: A Reinforcement Learning Approach also belongs on the bookshelves of anyone with an advanced interest in machine learning and artificial intelligence as it applies to the field of cooperative or competitive robotics.…

Codice articolo LU-9781119699033

Titolo
Multi-Agent Coordination
Autore
Amit Konar, Arup Kumar Sadhu
Editore
John Wiley and Sons Inc, US
Anno di pubblicazione
2020
Condizione
New
Rilegatura
Hardback
Lingua
inglese
ISBN 10
1119699037
ISBN 13
9781119699033
Peso dell'articolo
592 grammi

Rarewaves.com USA

London, London, Regno Unito

Venditore con 5 stelle

Venditore AbeBooks dal 11 giugno 2025

Tariffe di spedizione da Regno Unito a U.S.A.

ArticoloDa 9 a 14 giorni lavorativiDa 9 a 14 giorni lavorativi
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