Multi-agent machine learning : a reinforcement approach
by
 
Schwartz, Howard M., author.

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.

Subject Term
Reinforcement learning.
 
Differential games.
 
Swarm intelligence.
 
Machine learning.

Genre
Electronic books.

Electronic Access
Cover image http://catalogimages.wiley.com/images/db/jimages/9781118362082.jpg
 
Ebook 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


LibraryMaterial TypeItem BarcodeShelf Number[[missing key: search.ChildField.HOLDING]]Status
Online LibraryE-Book341941-1001ONLINE(341941.1)Elektronik Kütüphane