| LIBRARY OF CONGRESS CONTROL NUMBER |
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| LC control number |
2015047142 |
| INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781107134607 |
| DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Call number |
519.2/33 |
| MAIN ENTRY--PERSONAL NAME |
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| Authors |
Krishnamurthy, Vikram |
| TITLE STATEMENT |
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| Title |
Partially observed Markov decision processes : |
| Subtitle |
from filtering to controlled sensing |
| Statement of responsibility, etc |
Vikram Krishnamurthy |
| PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Place of publication |
Cambridge : |
| Publisher |
Cambridge University Press, |
| Date |
c2016. |
| PHYSICAL DESCRIPTION |
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| Extent |
xiii, 476 p. : |
| Other Details |
ill. ; |
| Size |
26 cm. |
| CONTENTS |
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| 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. |
| SUMMARY |
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| Summary |
This book covers formulation, algorithms, and structural results of partially observed Markov decision processes, linking theory to real-world applications in controlled sensing. |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Markov processes |
| Geographic |
Textbooks |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical Heading |
Stochastic processes |
| Geographic |
Textbooks |
| ELECTRONIC LOCATION AND ACCESS |
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| Uniform Resource Identifier |
https://uowd.box.com/s/tsxocw67f638sosi2wjho6dr0tt84g3j |
| Public note |
Location Map |
| MAIN ENTRY--PERSONAL NAME |
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| -- |
58710 |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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| -- |
58711 |
| SUBJECT ADDED ENTRY--TOPICAL TERM |
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58712 |