Deep reinforcement learning hands-on (Record no. 560553)

000 -LEADER
fixed length control field 02131 a2200217 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20190930155716.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190926b xxu||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781788834247
040 ## - CATALOGING SOURCE
Transcribing agency IIT Kanpur
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Item number L311d
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Lapan, Maxim
245 ## - TITLE STATEMENT
Title Deep reinforcement learning hands-on
Remainder of title apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, alphago zero and more
Statement of responsibility, etc Maxim Lapan
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Birmingham
Name of publisher Packet Publishing
Year of publication 2018
300 ## - PHYSICAL DESCRIPTION
Number of Pages xvi, 523p
520 ## - SUMMARY, ETC.
Summary, etc Key Features

Explore deep reinforcement learning (RL), from the first principles to the latest algorithms
Evaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithms
Keep up with the very latest industry developments, including AI-driven chatbots

Book Description

Recent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google's use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace.

Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments. Take on both the Atari set of virtual games and family favorites such as Connect4. The book provides an introduction to the basics of RL, giving you the know-how to code intelligent learning agents to take on a formidable array of practical tasks. Discover how to implement Q-learning on 'grid world' environments, teach your agent to buy and trade stocks, and find out how natural language models are driving the boom in chatbots.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Machine learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Reinforcement learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical Term Natural language processing (Computer science)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Damaged status Not for loan Collection code Permanent Location Current Location Date acquired Source of acquisition Cost, normal purchase price Full call number Accession Number Cost, replacement price Koha item type
        General Stacks P K Kelkar Library, IIT Kanpur P K Kelkar Library, IIT Kanpur 2019-10-09 62 2017.65 006.31 L311d A184819 2886.48 Books

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