Multi-Agent Machine Learning
H. M. Schwartz
John Wiley & Sons Inc, 2014
136,25 €On orderDelivery: 2-3 weeks
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.
- ISBN-13
- 9781118362082
- ISBN-10
- 111836208X
- Publisher
- John Wiley & Sons Inc
- Year
- 2014
- Publication date
- 2014-09-26
- Pages
- 256
- Dimensions
- 163x238x18
- Weight
- 478