你好! Shipping to Taiwan with premium packaging for just NT$300 

Ship to
Taiwan
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Multi-Agent Coordination: A Reinforcement Learning Approach (Wiley - Ieee)
Type
Physical Book
Author
Publisher
Year
2020
Language
English
Pages
320
Format
Hardcover
Dimensions
22.9x15.2x1.9 cm
Weight
0.59 kg.
ISBN13
9781119699033
Edition No.
1
Categories

Multi-Agent Coordination: A Reinforcement Learning Approach (Wiley - Ieee)

Amit Konar (Author) · Arup Kumar Sadhu (Author) · Wiley-IEEE Press · Hardcover

Multi-Agent Coordination: A Reinforcement Learning Approach (Wiley - Ieee) - Konar, Amit ; Sadhu, Arup Kumar

Cheaper New Book Imported to Taiwan
Delivery: 02 Oct - 12 Oct Shipping: 6 to 7 business days.
NT$ 4,462
Faster New Book Imported to Taiwan
Delivery: 01 Oct - 09 Oct Shipping: 5 to 6 business days.
NT$ 4,835
NT$ 4,462

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Multi-Agent Coordination: A Reinforcement Learning Approach (Wiley - Ieee) "

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 consensus Q-learning (CoQL), which addresses the equilibrium selection problem. Chapter 4 introduces a new dimension in the literature of the traditional correlated Q-learning (CQL), in which correlated equilibrium (CE) is computed partly in the learning and the rest in the planning phases, thereby requiring CE computation once only. Chapter 5 proposes an alternative solution to the multi-agent planning problem using meta-heuristic optimization algorithms. Chapter 6 provides the concluding remarks based on the principles and experimental results acquired in the previous chapters. Possible future directions of research are also examined briefly at the end of the chapter.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Hardcover.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews