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European Journal of Operational Research, 1989
The paper is an introduction to Markov decision processes mainly addressed to possible applicants. Therefore it presents a finite model only, but a broad variety of objectives, algorithms (e.g. aggregation), and extensions (e.g. semi-Markov, partially observed, adaptive multiobjective, and constrained models).
White, Chelsea C. III, White, Douglas J.
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The paper is an introduction to Markov decision processes mainly addressed to possible applicants. Therefore it presents a finite model only, but a broad variety of objectives, algorithms (e.g. aggregation), and extensions (e.g. semi-Markov, partially observed, adaptive multiobjective, and constrained models).
White, Chelsea C. III, White, Douglas J.
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Statistica Neerlandica, 1985
AbstractA review is presented of the development over the years of the theory and practical use of Markov decision processes. To this purpose three periods are considered: before 1966, from 1966 till 1972, and after 1973. In all 3 periods there has been some contribution from the Netherlands, but particularly in the last period the research in the ...
Wal, van der, J., Wessels, J.
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AbstractA review is presented of the development over the years of the theory and practical use of Markov decision processes. To this purpose three periods are considered: before 1966, from 1966 till 1972, and after 1973. In all 3 periods there has been some contribution from the Netherlands, but particularly in the last period the research in the ...
Wal, van der, J., Wessels, J.
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2012
Markov chains are useful in describing many discrete event stochastic processes; however, they are not exible enough to model situations where we have to make decisions to control the future trajectories of the system. For this reason, the theory of Markov decision processes (MDPs), also known as controlled Markov chains, has been developed.
Vivek S. Borkar +3 more
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Markov chains are useful in describing many discrete event stochastic processes; however, they are not exible enough to model situations where we have to make decisions to control the future trajectories of the system. For this reason, the theory of Markov decision processes (MDPs), also known as controlled Markov chains, has been developed.
Vivek S. Borkar +3 more
openaire +2 more sources
Markov Decision Process Measurement Model
Psychometrika, 2018Within-task actions can provide additional information on student competencies but are challenging to model. This paper explores the potential of using a cognitive model for decision making, the Markov decision process, to provide a mapping between within-task actions and latent traits of interest. Psychometric properties of the model are explored, and
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