Overview
- Presents recent research in sample efficient multiagent learning in the presence of markovian agents
- Develops multiagent learning algorithms not previously been achieved
- Takes steps towards building completely autonomous learning algorithms
Part of the book series: Studies in Computational Intelligence (SCI, volume 523)
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Table of contents (9 chapters)
Keywords
About this book
Reviews
From the book reviews:
“The book presents the PhD findings of the author in the field of multiagent learning. … All the concepts are thoroughly described and accompanied by theoretical analysis and empirical testing. A book suitable for researchers working in multiagent learning and game theory.” (Ruxandra Stoean, zbMATH, Vol. 1288, 2014)
Authors and Affiliations
Bibliographic Information
Book Title: Sample Efficient Multiagent Learning in the Presence of Markovian Agents
Authors: Doran Chakraborty
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-02606-0
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-02605-3Published: 11 October 2013
Softcover ISBN: 978-3-319-35293-0Published: 23 August 2016
eBook ISBN: 978-3-319-02606-0Published: 30 September 2013
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVIII, 147
Number of Illustrations: 31 b/w illustrations