Constrained dynamic programming with two discount factors: applications and an algorithm

We consider a discrete time Markov decision process, where the objectives are linear combinations of standard discounted rewards, each with a different discount factor. We describe several applications that motivate the recent interest in these criteria. For the special case where a standard discoun...

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Bibliographic Details
Published inIEEE transactions on automatic control Vol. 44; no. 3; pp. 628 - 631
Main Authors Feinberg, E.A., Shwartz, A.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.03.1999
Institute of Electrical and Electronics Engineers
Subjects
Algorithms
Applied sciences
Automatic control
Computer performance
Cost engineering
Cost function
Criteria
Discounts
Dynamic programming
Electronic mail
Exact sciences and technology
Heuristic algorithms
Markov processes
Mathematical programming
Operational research and scientific management
Operational research. Management science
Optimization
Optimization. Search problems
Power system management
Random access memory
Read-write memory
Space technology
Stochastic processes
Markov process
Discounting
Markov decision
Dynamic programming
Constrained optimization
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ISSN0018-9286
DOI10.1109/9.751365

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Summary:We consider a discrete time Markov decision process, where the objectives are linear combinations of standard discounted rewards, each with a different discount factor. We describe several applications that motivate the recent interest in these criteria. For the special case where a standard discounted cost is to be minimized, subject to a constraint on another standard discounted cost but with a different discount factor, we provide an implementable algorithm for computing an optimal policy.
Bibliography:ObjectType-Article-2
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ISSN:0018-9286
DOI:10.1109/9.751365