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AuthorGheorghe, Adrian V. author
TitleDecision Processes in Dynamic Probabilistic System [electronic resource] / by Adrian V. Gheorghe
ImprintDordrecht : Springer Netherlands, 1990
Connect tohttp://dx.doi.org/10.1007/978-94-009-0493-4
Descript 376 p. online resource

CONTENT

1 Semi-Markov and Markov Chains -- 1.1 Definitions and basic properties -- 1.2 Algebraic and analytical methods in the study of Markovian systems -- 1.3 Transient and recurrent processes -- 1.4 Markovian populations -- 1.5 Partially observable Markov chains -- 1.6 Rewards and discounting -- 1.7 Models and applications -- 1.8 Dynamic-decision models for clinical diagnosis -- 2 Dynamic and Linear Programming -- 2.1 Discrete dynamic programming -- 2.2 A linear programming formulation and an algorithm for computation -- 3 Utility Functions and Decisions under Risk -- 3.1 Informational lotteries and axioms for utility functions -- 3.2 Exponential utility functions -- 3.3 Decisions under risk and uncertainty; event trees -- 3.4 Probability encoding -- 4 Markovian Decision Processes (Semi-Markov and Markov) with Complete Information (Completely Observable) -- 4.1 Value iteration algorithm (the finite horizon case) -- 4.2 Policy iteration algorithm (the finite horizon optimization) -- 4.3 Policy iteration with discounting -- 4.4 Optimization algorithm using linear programming -- 4.5 Risk-sensitive decision processes -- 4.6 On eliminating sub-optimal decision alternatives in Markov and semi-Markov decision processes -- 5 Partially Observable Markovian Decision Processes -- 5.1 Finite horizon partially observable Markov decision processes -- 5.2 The infinite horizon with discounting for partially observable Markov decision processes -- 5.3 A useful policy iteration algorithm, for discounted (? < 1) partially observable Markov decision processes -- 5.4 The infinite horizon without discounting for partially observable Markov processes -- 5.5 Partially observable semi-Markov decision processes -- 5.6 Risk-sensitive partially observable Markov decision processes -- 6 Policy Constraints in Markov Decision Processes -- 6.1 Methods of investigating policy costraints in Markov decision processes -- 6.2 Markov decision processes with policy constraints -- 6.3 Risk-sensitive Markov decision process with policy constraints -- 7 Applications -- 7.1 The emergency repair control for electrical power systems -- 7.2 Stochastic models for evaluation of inspection and repair schedules [2] -- 7.3 A Markovian dicision model for clinical diagnosis and treatment applied to the respiratory system


Mathematics Operations research Decision making System theory Probabilities Mathematics Probability Theory and Stochastic Processes Operation Research/Decision Theory Systems Theory Control



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