Results 61 to 70 of about 26,957 (159)
Monitored Markov Decision Processes
International Joint Conference on Autonomous Agents and Multiagent SystemsIn reinforcement learning (RL), an agent learns to perform a task by interacting with an environment and receiving feedback (a numerical reward) for its actions. However, the assumption that rewards are always observable is often not applicable in real-world problems. For example, the agent may need to ask a human to supervise its actions or activate a
Simone Parisi +4 more
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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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Bounds for Synchronizing Markov Decision Processes
, 2022 We consider Markov decision processes with synchronizing objectives, which require that a probability mass of $1-ε$ accumulates in a designated set of target states, either once, always, infinitely often, or always from some point on, where $ε= 0$ for sure synchronizing, and $ε\to 0$ for almost-sure and limit-sure synchronizing.
Doyen, Laurent, van den Bogaard, Marie
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Portfolio allocation under the vendor managed inventory: A Markov decision process
Journal of Applied Sciences and Environmental Management, 2017 Markov decision processes have been applied in solving a wide range of optimization problems over the years. This study provides a review of Markov decision processes and investigates its suitability for solutions to portfolio allocation problems under ...
VO Ezugwu, LI Igbinosun
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IEEE Access, 2018 In recent years, reinforcement learning (RL) has achieved remarkable success due to the growing adoption of deep learning techniques and the rapid growth of computing power.
Tuyen P. Le +2 more
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The value functions of Markov decision processes
Operations Research Letters, 2016 We provide a full characterization of the set of value functions of Markov decision processes.
Ehud Lehrer, Eilon Solan, Omri N. Solan
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Undiscounted Semi-Markov Decision Processes with Countably Infinite Action Spaces
AlgorithmsIn this article, we study semi-Markov decision processes (SMDPs) under the limiting ratio average (undiscounted) pay-off criterion, where the state space is finite and the action space of the decision maker is possibly countably infinite.
Kushal Guha Bakshi +4 more
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A Version of the Euler Equation in Discounted Markov Decision Processes
Journal of Applied Mathematics, 2012 This paper deals with Markov decision processes (MDPs) on Euclidean spaces with an infinite horizon. An approach to study this kind of MDPs is using the dynamic programming technique (DP).
H. Cruz-Suárez +2 more
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Multiple-Environment Markov Decision Processes
CoRR, 2014 info:eu-repo/semantics ...
Raskin, Jean-François, Sankur, Ocan
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Detection of Text Lines of Handwritten Arabic Manuscripts using Markov Decision Processes
International Journal of Interactive Multimedia and Artificial Intelligence, 2016 In a character recognition systems, the segmentation phase is critical since the accuracy of the recognition depend strongly on it. In this paper we present an approach based on Markov Decision Processes to extract text lines from binary images of Arabic
Youssef Boulid +2 more
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