Multi-Agent Coordination: A Reinforcement Learning Approach


Multi-Agent Coordination: A Reinforcement Learning Approach (Wiley - IEEE)
Part of: Wiley - IEEE (21 Books) | by 作者: Arup Kumar Sadhu and Amit Konar
Publisher Finelybook 出版社: Wiley-IEEE Press; 1st edition (December 3,2020)
Language 语言: English
pages 页数: 320 pages
ISBN-10 书号: 1119699037
ISBN-13 书号: 9781119699033


Book Description
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 作者: 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 作者: reinforcement learning and evolutionary algorithms,including topics like the Nash equilibrium and correlated equilibrium
Improving convergence speed of multi-agent Q-learning for cooperative task planning
Consensus Q-learning for multi-agent cooperative planning
The efficient computing of correlated equilibrium for cooperative q-learning based multi-agent planning
A 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.


下载地址:

Multi-Agent Coordination 9781119699033.rar

下载地址 Download
打赏
未经允许不得转载:finelybook » Multi-Agent Coordination: A Reinforcement Learning Approach

相关推荐

  • 暂无文章

评论 抢沙发

  • 昵称 (必填)
  • 邮箱 (必填)
  • 网址

觉得文章有用就打赏一下

您的打赏,我们将继续给力更多优质内容

支付宝扫一扫打赏

微信扫一扫打赏