Handbook of Markov Decision Processes

Methods and Applications

Häftad, Engelska, 2012

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1.1 AN OVERVIEW OF MARKOV DECISION PROCESSES The theory of Markov Decision Processes-also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming-studiessequential optimization ofdiscrete time stochastic systems.

Produktinformation

Utgivningsdatum2012-10-29
Mått155 x 235 x 31 mm
Vikt861 g
FormatHäftad
SpråkEngelska
SerieInternational Series in Operations Research & Management Science
Antal sidor565
FörlagSpringer-Verlag New York Inc.
ISBN9781461352488

Tillhör följande kategorier

1 Introduction.- I Finite State and Action Models.- 2 Finite State and Action MDPs.- 3 Bias Optimality.- 4 Singular Perturbations of Markov Chains and Decision Processes.- II Infinite State Models.- 5 Average Reward Optimization Theory for Denumerable State Spaces.- 6 Total Reward Criteria.- 7 Mixed Criteria.- 8 Blackwell Optimality.- 9 The Poisson Equation for Countable Markov Chains: Probabilistic Methods and Interpretations.- 10 Stability, Performance Evaluation, and Optimization.- 11 Convex Analytic Methods in Markov Decision Processes.- 12 The Linear Programming Approach.- 13 Invariant Gambling Problems and Markov Decision Processes.- III Applications.- 14 Neuro-Dynamic Programming: Overview and Recent Trends.- 15 Markov Decision Processes in Finance and Dynamic Options.- 16 Applications of Markov Decision Processes in Communication Networks.- 17 Water Reservoir Applications of Markov Decision Processes.