Markov Decision Processes: Discrete Stochastic Dynamic Programming

1. Introduction.

2. Model Formulation.

3. Examples.

4. Finite-Horizon Markov Decision Processes.

5. Infinite-Horizon Models: Foundations.

6. Discounted Markov Decision Problems.

7. The Expected Total-Reward. Criterion.

8. Average Reward and Related Criteria.

9. The Average Reward Criterion-Multichain and Communicating Models.

10. Sensitive Discount Optimality.

11. Continuous-Time Models.

Afterword.

Notation.

Appendix A. Markov Chains.

Appendix B. Semicontinuous Functions.

Appendix C. Normed Linear Spaces.

Appendix D. Linear Programming.

Bibliography.

Index.