Results 11 to 20 of about 9,481,834 (176)
Inference Strategies for Solving Semi-Markov Decision Processes
, 2012 Semi-Markov decision processes are used to formulate many control problems and also play a key role in hierarchical reinforcement learning. In this chapter we show how to translate the decision making problem into a form that can instead be solved by inference and learning techniques.
Hoffman, M, de Freitas, N
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The exponential cost optimality for finite horizon semi-Markov decision processes [PDF]
, 2022 summary:This paper considers an exponential cost optimality problem for finite horizon semi-Markov decision processes (SMDPs). The objective is to calculate an optimal policy with minimal exponential costs over the full set of policies in a finite ...
Wen, Xian, Huo, Haifeng
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Optimal maintenance of deteriorating equipment using semi-Markov decision processes and linear programming [PDF]
International Journal of Industrial Engineering and ManagementThis paper considers a mathematical model analysing the deterioration of system equipment and available maintenance options. Under specific conditions on costs and transition probabilities of the model, the issue of ideal maintenance of the equipment by ...
Giannis Kechagias +3 more
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Risk probability optimization problem for finite horizon continuous time Markov decision processes with loss rate [PDF]
, 2021 summary:This paper presents a study the risk probability optimality for finite horizon continuous-time Markov decision process with loss rate and unbounded transition rates.
Wen, Xian, Huo, Haifeng
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A Fast-Pivoting Algorithm for Whittle’s Restless Bandit Index
Mathematics, 2020 The Whittle index for restless bandits (two-action semi-Markov decision processes) provides an intuitively appealing optimal policy for controlling a single generic project that can be active (engaged) or passive (rested) at each decision epoch, and ...
José Niño-Mora
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Recursive Markov Decision Processes and Recursive Stochastic Games [PDF]
, 2005 We introduce Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs), and study the decidability and complexity of algorithms for their analysis and verification.
Mihalis Yannakakis +3 more
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Reactive Reinforcement Learning in Asynchronous Environments
Frontiers in Robotics and AI, 2018 The relationship between a reinforcement learning (RL) agent and an asynchronous environment is often ignored. Frequently used models of the interaction between an agent and its environment, such as Markov Decision Processes (MDP) or Semi-Markov Decision
Jaden B. Travnik +6 more
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Symbolic Magnifying Lens Abstraction in Markov Decision Processes [PDF]
, 2008 In this paper, we combine abstraction-refinement and symbolic techniques to fight the state-space explosion problem when model checking Markov decision processes (MDPs).
Luca de Alfaro +7 more
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MATEC Web of Conferences, 2018 In the article a common semi-Markov mathematical model is considered that allows one to investigate the productivity and reliability of various technological processes of mechanical assembly production.
Rapatskiy Yuri +5 more
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Hierarchical dialogue optimization using semi-Markov decision processes [PDF]
Interspeech 2007, 2007 This paper addresses the problem of dialogue optimization on large search spaces. For such a purpose, in this paper we propose to learn dialogue strategies using multiple Semi-Markov Decision Processes and hierarchical reinforcement learning. This approach factorizes state variables and actions in order to learn a hierarchy of policies. Our experiments
Cuayáhuitl, Heriberto +3 more
openaire +3 more sources