Description

Book Synopsis
This book is an up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. The concentration of the book is on infinite-horizon discrete-time models, and it also discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models.

Table of Contents
Preface.

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.

Markov Decision Processes

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    A Paperback / softback by Martin L. Puterman

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      Publisher: John Wiley & Sons Inc
      Publication Date: 25/02/2005
      ISBN13: 9780471727828, 978-0471727828
      ISBN10: 0471727822
      Also in:
      Mathematics

      Description

      Book Synopsis
      This book is an up-to-date, unified and rigorous treatment of theoretical, computational and applied research on Markov decision process models. The concentration of the book is on infinite-horizon discrete-time models, and it also discusses arbitrary state spaces, finite-horizon and continuous-time discrete-state models.

      Table of Contents
      Preface.

      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.

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