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Partially observed Markov decision processes : from filtering to controlled sensing / Vikram Krishnamurthy, University of British Columbia.
Author
Krishnamurthy, V. (Vikram)
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Format
Book
Language
English
Published/Created
Cambridge : Cambridge University Press, 2016.
Description
xiii, 476 pages : illustrations ; 26 cm
Availability
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Call Number
Status
Location Service
Notes
Engineering Library - Stacks
QA274.7 .K75 2016
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Details
Subject(s)
Markov processes
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Textbooks
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Stochastic processes
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Summary note
This book covers formulation, algorithms, and structural results of partially observed Markov decision processes, linking theory to real-world applications in controlled sensing.
Bibliographic references
Includes bibliographical references (pages 455-470) and index.
Contents
Preface; 1. Introduction; Part I. Stochastic Models and Bayesian Filtering: 2. Stochastic state-space models; 3. Optimal filtering; 4. Algorithms for maximum likelihood parameter estimation; 5. Multi-agent sensing: social learning and data incest; Part II. Partially Observed Markov Decision Processes. Models and Algorithms: 6. Fully observed Markov decision processes; 7. Partially observed Markov decision processes (POMDPs); 8. POMDPs in controlled sensing and sensor scheduling; Part III. Partially Observed Markov Decision Processes: 9. Structural results for Markov decision processes; 10. Structural results for optimal filters; 11. Monotonicity of value function for POMPDs; 12. Structural results for stopping time POMPDs; 13. Stopping time POMPDs for quickest change detection; 14. Myopic policy bounds for POMPDs and sensitivity to model parameters; Part IV. Stochastic Approximation and Reinforcement Learning: 15. Stochastic optimization and gradient estimation; 16. Reinforcement learning; 17. Stochastic approximation algorithms: examples; 18. Summary of algorithms for solving POMPDs; Appendix A. Short primer on stochastic simulation; Appendix B. Continuous-time HMM filters; Appendix C. Markov processes; Appendix D. Some limit theorems; Bibliography; Index.
ISBN
9781107134607 ((hbk.))
1107134609 ((hbk.))
LCCN
2015047142
OCLC
933719599
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