カゴの中を見る

商品数:0点

合計:0円

カゴの中を見る

商品を探す

商品カテゴリから選ぶ

商品名を入力

検索結果で出ない商品は

お問い合わせ下さいませ

商品カテゴリ

分野別

商品コード: 9781886529397

Reinforcement Learning and Optimal Control

販売価格(税込10%): 16,179 円
在庫数: 在庫あり
関連カテゴリ:

分野別 > 数学 > 応用数学

特集 > 計画数理

数  量

カゴに入れる

商品おすすめポイント

書名

Reinforcement Learning and Optimal Control
著者・編者 Bertsekas, D.P.
出版社/発行元 Athena Scientific
発行年/月 2019年7月   
装丁 Hardcover
ページ数/巻数 388 ページ
ISBN 978-1-886529-39-7
発送予定 1-3営業日内に発送致します

 

Description

 

This book considers large and challenging multistage decision problems, which can be solved in principle by dynamic programming (DP), but their exact solution is computationally intractable. We discuss solution methods that rely on approximations to produce suboptimal policies with adequate performance. These methods are collectively known by several essentially equivalent names: reinforcement learning, approximate dynamic programming, and neuro-dynamic programming. They have been at the forefront of research for the last 25 years, and they underlie, among others, the recent impressive successes of self-learning in the context of games such as chess and Go.

 

Our subject has benefited greatly from the interplay of ideas from optimal control and from artificial intelligence, as it relates to reinforcement learning and simulation-based neural network methods. One of the aims of the book is to explore the common boundary between these two fields and to form a bridge that is accessible by workers with background in either field. Another aim is to organize coherently the broad mosaic of methods that have proved successful in practice while having a solid theoretical and/or logical foundation. This may help researchers and practitioners to find their way through the maze of competing ideas that constitute the current state of the art.

 

数  量

カゴに入れる

この商品に対するお客様の声

 

 

mitsumori

見積書をお送り致します

 

 

  新刊案内など配信中!!

 

このページのTOPへ