MARC details
000 -LEADER |
fixed length control field |
01676cam a2200265 i 4500 |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20160322165210.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
140604t20142014njua b 001 0 eng |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781118362082 (hardback) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
111836208X (hardback) |
041 ## - LANGUAGE CODE |
Language code of text/sound track or separate title |
eng |
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
004.85 |
Item number |
SCH |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Schwartz, Howard M., |
9 (RLIN) |
2400 |
245 10 - TITLE STATEMENT |
Title |
Multi-agent machine learning : |
Remainder of title |
a reinforcement approach / |
Statement of responsibility, etc. |
Howard M. Schwartz, Department of Systems and Computer Engineering, Carleton University. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc. |
New Jersey: |
Name of publisher, distributor, etc. |
Wiley, |
Date of publication, distribution, etc. |
2014. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xi, 242 pages : |
520 ## - SUMMARY, ETC. |
Summary, etc. |
"Multi-Agent Machine Learning: A Reinforcement Learning Approach is a framework to understanding different methods and approaches in multi-agent machine learning. It also provides cohesive coverage of the latest advances in multi-agent differential games and presents applications in game theory and robotics. Framework for understanding a variety of methods and approaches in multi-agent machine learning. Discusses methods of reinforcement learning such as a number of forms of multi-agent Q-learning Applicable to research professors and graduate students studying electrical and computer engineering, computer science, and mechanical and aerospace engineering"-- |
520 ## - SUMMARY, ETC. |
Summary, etc. |
"Provide an in-depth coverage of multi-player, differential games and Gam theory"-- |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Reinforcement learning. |
9 (RLIN) |
2401 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Differential games. |
9 (RLIN) |
2402 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Swarm intelligence. |
9 (RLIN) |
2403 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Machine learning. |
9 (RLIN) |
55 |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
TECHNOLOGY & ENGINEERING / Electronics / General. |
9 (RLIN) |
230 |
856 42 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="http://catalogimages.wiley.com/images/db/jimages/9781118362082.jpg">http://catalogimages.wiley.com/images/db/jimages/9781118362082.jpg</a> |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Koha item type |
Books |