Multi-Agent Machine Learning: A Reinforcement Approach
H. M. Schwartz
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
Categorías:
Año:
2014
Edición:
1
Editorial:
Wiley
Idioma:
english
Páginas:
256
ISBN 10:
111836208X
ISBN 13:
9781118362082
Archivo:
EPUB, 13.03 MB
IPFS:
,
english, 2014