Multi–Agent Machine Learning – A Reinforcement Approach
Autor HM Schwartzen Limba Engleză Hardback – 25 sep 2014
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Specificații
ISBN-13: 9781118362082
ISBN-10: 111836208X
Pagini: 256
Dimensiuni: 156 x 234 x 15 mm
Greutate: 0.48 kg
Ediția:New.
Editura: Wiley
Locul publicării:Hoboken, United States
ISBN-10: 111836208X
Pagini: 256
Dimensiuni: 156 x 234 x 15 mm
Greutate: 0.48 kg
Ediția:New.
Editura: Wiley
Locul publicării:Hoboken, United States
Public țintă
Primary: university researchers and graduate students in electrical and computer engineering, computer science and mechanical aerospace engineering. Also, researchers in behavioural economics. Secondary: researchers in the aerospace and manufacturing industry, as well as the automotive and robotics industries.Cuprins
Notă biografică
Howard M. Schwartz, PhD, received his B.Eng. Degree from McGill University, Montreal, Canada in une 1981 and his MS Degree and PhD Degree from MIT, Cambridge, USA in 1982 and 1987 respectively. He is currently a professor in systems and computer engineering at Carleton University, Canada. His research interests include adaptive and intelligent control systems, robotic, artificial intelligence, system modelling, system identification, and state estimation.
Descriere
The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces.