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
:
Library | Material Type | Item Barcode | Shelf Number | [[missing key: search.ChildField.HOLDING]] | Status |
---|
Online Library | E-Book | 341941-1001 | ONLINE(341941.1) | | Elektronik Kütüphane |