Results 251 to 260 of about 152,215 (282)

Obtaining a Continuous Time Markov Decision Process from Statecharts

2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009
This paper proposes a strategy to associate Statecharts with a Markov Decision Process for performance evaluation. Statecharts are adapted to represent the possible decision choices and the costs incurred from decisions. Markov Decision Process is used to evaluate the long term effects of decisions.
Marcelino S. da Silva, Adamo L. Santana, Carlos R. L. Frances, Nandamudi L. Vijaykumar, Solon V. Carvalho   +4 more
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Bounded Aggregation for Continuous Time Markov Decision Processes

2017
Markov decision processes suffer from two problems, namely the so-called state space explosion which may lead to long computation times and the memoryless property of states which limits the modeling power with respect to real systems. In this paper we combine existing state aggregation and optimization methods for a new aggregation based optimization ...
Peter Buchholz, Iryna Dohndorf, Alexander Frank, Dimitri Scheftelowitsch   +3 more
openaire   +1 more source

Risk-Sensitive Discounted Continuous-Time Markov Decision Processes with Unbounded Rates

SIAM Journal on Control and Optimization, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xianping Guo, Zhong-Wei Liao
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Continuous time shock markov decision processes with discounted criterion

Optimization, 1992
This paper presents a new concept of Markov decision processes: continuous time shock Markov decision processes, which model Markovian controlled systems sequentially shocked by its environment. Between two adjacent shocks, the system can be modeled by continuous time Markov decision processes.
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Numerical Approximations for Discounted Continuous Time Markov Decision Processes

2019
This paper deals with a continuous-time Markov decision process M, with Borel state and action spaces, under the total expected discounted cost optimality criterion. By suitably approximating an underlying probability measure with a measure with finite support and by discretizing the action sets of the control model, we can construct a finite state and
Dufour, François, Prieto-Rumeau, Tomás
openaire   +2 more sources

Continuous-Time Markov Decision Processes

2020
Alexey Piunovskiy, Yi Zhang
openaire   +1 more source

Continuous-Time Markov Decision Processes

2009
Xianping Guo, Onésimo Hernández-Lerma
openaire   +2 more sources

A Continuous-Time Markov Decision Process for Infrastructure Surveillance

2011
We consider the dynamics of threat of an infrastructure consisting of various sectors. The dynamics are modelled by a continuous-time Markov decision process (CMDP). A key property of the model is that dependencies between sectors are taken into account. The actions are determined by the number of the available security staff. The decision maker has to
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Finite approximation for finite-horizon continuous-time Markov decision processes

4OR, 2016
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Markov Decision Processes With Continuous Time Parameter.

Journal of the American Statistical Association, 1985
Martin L. Puterman, F. A. Van der Duyn Schouten   +1 more
openaire   +1 more source