Title:
Multi-agent machine learning : a reinforcement approach
Author:
Schwartz, Howard M., author.
ISBN:
9781118884614
9781118884478
9781322094762
Physical Description:
1 online resource (xi, 242 pages)
Abstract:
"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"-- Provided by publisher.
"Provide an in-depth coverage of multi-player, differential games and Gam theory"-- Provided by publisher.
Genre:
Electronic Access:
Cover image http://catalogimages.wiley.com/images/db/jimages/9781118362082.jpgEbook Library http://public.eblib.com/choice/publicfullrecord.aspx?p=1775207
ebrary http://site.ebrary.com/id/10921255
John Wiley http://dx.doi.org/10.1002/9781118884614
MyiLibrary http://www.myilibrary.com?id=640727
http://swb.eblib.com/patron/FullRecord.aspx?p=1775207
Copies:
Available:*
Library | Material Type | Item Barcode | Shelf Number | Status | Item Holds |
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Searching... | E-Book | 341941-1001 | ONLINE(341941.1) | Searching... | Searching... |