Control Optimization with Stochastic Dynamic Programming
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 25)
This chapter focuses on a problem of control optimization — namely, the Markov decision problem. Our discussions will be at a very elementary level, and we will not attempt to prove any theorems.
KeywordsTransition Probability Matrix Stochastic Game Bellman Equation Policy Iteration Average Reward
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© Springer Science+Business Media New York 2003