Foundations of Deep Reinforcement Learning : Theory and Practice in Python (Record no. 51474)
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000 -LEADER | |
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fixed length control field | 01366 a2200181 4500 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20250912103745.0 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9789390394852 |
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.31 GRA |
100 ## - MAIN ENTRY--PERSONAL NAME | |
Personal name | Graesser, Laura |
245 ## - TITLE STATEMENT | |
Title | Foundations of Deep Reinforcement Learning : Theory and Practice in Python |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Name of publisher, distributor, etc | Pearson India Education Services Pvt. Ltd. |
Place of publication, distribution, etc | Noida |
Date of publication, distribution, etc | 2022 |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 379 |
520 ## - SUMMARY, ETC. | |
Summary, etc | Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games-such as Go, Atari games, and DotA 2-to robotics.<br/><br/><br/>Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work.<br/><br/>This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python. |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial intelligence |
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Deep learning |
700 ## - ADDED ENTRY--PERSONAL NAME | |
Personal name | Keng, Wah Loon |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | Book |
Source of classification or shelving scheme | Dewey Decimal Classification |
No items available.