Results 51 to 60 of about 709,572 (229)
A reinforcement learning based decision support system in textile manufacturing process
, 2020 This paper introduced a reinforcement learning based decision support system in textile manufacturing process. A solution optimization problem of color fading ozonation is discussed and set up as a Markov Decision Process (MDP) in terms of tuple {S, A, P,
He, Zhenglei +4 more
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Evidential Decision Theory via Partial Markov Categories [PDF]
arXiv, 2023 We introduce partial Markov categories. In the same way that Markov categories encode stochastic processes, partial Markov categories encode stochastic processes with constraints, observations and updates. In particular, we prove a synthetic Bayes theorem; we apply it to define a syntactic partial theory of observations on any Markov category, whose ...
arxiv
Absorbing Markov decision processes
ESAIM: Control, Optimisation and Calculus of VariationsIn this paper, we study discrete-time absorbing Markov Decision Processes (MDP) with measurable state space and Borel action space with a given initial distribution. For such models, solutions to the characteristic equation that are not occupation measures may exist.
Dufour, François, Prieto-Rumeau, Tomás
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Multi-model Markov decision processes
IISE Transactions, 2021 Markov decision processes (MDPs) have found success in many application areas that involve sequential decision making under uncertainty, including the evaluation and design of treatment and screening protocols for medical decision making. However, the data used to parameterize the model can influence what policies are recommended, and multiple ...
Lauren N. Steimle +2 more
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Taming denumerable Markov decision processes with decisiveness [PDF]
arXiv, 2020 Decisiveness has proven to be an elegant concept for denumerable Markov chains: it is general enough to encompass several natural classes of denumerable Markov chains, and is a sufficient condition for simple qualitative and approximate quantitative model checking algorithms to exist.
arxiv
Data-Driven Volt/VAR Optimization for Modern Distribution Networks: A Review
IEEE AccessThe Volt/Var optimization (VVO) enables advanced control strategy development for voltage regulation. With the recent advancement of data-driven approaches and communication infrastructure, realtime decision-making through VVO can effectively address ...
Sarah Allahmoradi +4 more
doaj +1 more source
Experts in a Markov Decision Process [PDF]
, 2004 We consider an MDP setting in which the reward function is allowed to change during each time step of play (possibly in an adversarial manner), yet the dynamics remain fixed.
Even-Dar, Eyal +2 more
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Quantile Markov Decision Process
, 2017 The goal of a traditional Markov decision process (MDP) is to maximize expected cumulativereward over a defined horizon (possibly infinite). In many applications, however, a decision maker may beinterested in optimizing a specific quantile of the cumulative reward instead of its expectation.
Li, X, Zhong, H, Brandeau, M
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A limit theorem for Markov decision processes [PDF]
Journal of Dynamics & Games, 2013 In this paper we prove a deterministic approximation theorem for a sequence of Markov decision processes with finitely many actions and general state spaces as they appear frequently in economics, game theory and operations research. Using viscosity solution methods no a-priori differentiabililty assumptions are imposed on the value function ...
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Scalable Verification of Markov Decision Processes [PDF]
, 2015 V4: FMDS version, 12 pages, 4 ...
Legay, Axel +2 more
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