MARC details
| 000 -LEADER |
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| fixed length control field |
02043nam a2200301Ia 4500 |
| 000 - LEADER |
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| fixed length control field |
02501nam a22003375i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
978-3-031-37345-9 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20240319120942.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
230814s2023 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783031373459 |
| -- |
978-3-031-37345-9 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
6.31 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Ris-Ala, Rafael. |
| 9 (RLIN) |
33579 |
| 245 ## - TITLE STATEMENT |
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| Title |
Fundamentals of Reinforcement Learning |
| Statement of responsibility, etc. |
by Rafael Ris-Ala. |
| Medium |
[electronic resource] / |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st ed. 2023. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
Cham |
| Name of publisher, distributor, etc. |
Springer Nature Switzerland |
| Date of publication, distribution, etc. |
2023 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XV, 88 p. 94 illus., 87 illus. in color. |
| Other physical details |
online resource. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
Artificial intelligence (AI) applications bring agility and modernity to our lives, and the reinforcement learning technique is at the forefront of this technology. It can outperform human competitors in strategy games, creative compositing, and autonomous movement. Moreover, it is just starting to transform our civilization. This book provides an introduction to AI, specifies machine learning techniques, and explores various aspects of reinforcement learning, approaching the latest concepts in a didactic and illustrated manner. It is aimed at students who want to be part of technological advances and professors engaged in the development of innovative applications, helping with academic and industrial challenges. Understanding the Fundamentals of Reinforcement Learning will allow you to: Understand essential AI concepts Gain professional experience Interpret sequential decision problems and solve them with reinforcement learning Learn how the Q-Learning algorithm works Practice with commented Python code Find advantageous directions. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Artificial intelligence. |
| 9 (RLIN) |
33580 |
|
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| Topical term or geographic name entry element |
Artificial Intelligence. |
| 9 (RLIN) |
33581 |
|
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| Topical term or geographic name entry element |
Machine learning. |
| 9 (RLIN) |
33582 |
|
|---|
| Topical term or geographic name entry element |
Machine Learning. |
| 9 (RLIN) |
33583 |
|
|---|
| Topical term or geographic name entry element |
Software engineering. |
| 9 (RLIN) |
33584 |
|
|---|
| Topical term or geographic name entry element |
Software Engineering. |
| 9 (RLIN) |
33585 |
| 856 ## - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="https://doi.org/10.1007/978-3-031-37345-9">https://doi.org/10.1007/978-3-031-37345-9</a> |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Koha item type |
e-Book |
| Source of classification or shelving scheme |
Dewey Decimal Classification |
