Handbook of Markov Decision Processes: Methods and Applications - Tapa blanda

Sinopsis

1. Introduction; E.A. Feinberg, A. Shwartz. Part I: Finite State and Action Models. 2. Finite State and Action MDPs; L. Kallenberg. 3. Bias Optimality; M.E. Lewis, M.L. Puterman. 4. Singular Perturbations of Markov Chains and Decision Processes; K.E. Avrachenkov, et al. Part II: Infinite State Models. 5. Average Reward Optimization Theory for Denumerable State Spaces; L.I. Sennott. 6. Total Reward Criteria; E.A. Feinberg. 7. Mixed Criteria; E.A. Feinberg, A. Shwartz. 8. Blackwell Optimality; A. Hordijk, A.A. Yushkevich. 9. The Poisson Equation for Countable Markov Chains: Probabilistic Methods and Interpretations; A.M. Makowski, A. Shwartz. 10. Stability, Performance Evaluation, and Optimization; S.P. Meyn. 11. Convex Analytic Methods in Markov Decision Processes; V.S. Borkar. 12. The Linear Programming Approach; O. Hernández-Lerma, J.B. Lasserre. 13. Invariant Gambling Problems and Markov Decision Processes; L.E. Dubins, et al. Part III: Applications. 14. Neuro-Dynamic Programming: Overview and Recent Trends; B. Van Roy. 15. Markov Decision Processes in Finance and Dynamic Options; M. Schäl. 16. Applications of Markov Decision Processes in Communication Networks; E. Altman. 17. Water Reservoir Applications of Markov Decision Processes; B.F. Lamond, A. Boukhtouta. Index.

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