Control Optimization with Stochastic Dynamic Programming

  • Abhijit Gosavi
Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 25)

Abstract

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.

Keywords

Transition 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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Copyright information

© Springer Science+Business Media New York 2003

Authors and Affiliations

  • Abhijit Gosavi
    • 1
  1. 1.Department of Industrial EngineeringThe State University of New YorkBuffaloUSA

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