Inference Strategies for Solving Semi-Markov Decision Processes [PDF]
, 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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Mixed Markov Decision Processes in a Semi-Markov Environment with Discounted Criterion [PDF]
Journal of Mathematical Analysis and Applications, 1998 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hu, Qiying, Wang, Jinling
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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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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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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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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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Efficient qualitative analysis of classes of recursive markov decision processes and simple stochastic games [PDF]
, 2006 . Recursive Markov Decision Processes (RMDPs) and Recursive Simple Stochastic Games (RSSGs) are natural models for recursive systems involving both probabilistic and non-probabilistic actions.
Mihalis Yannakakis +3 more
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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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Bounded parameter Markov decision processes with average reward criterion [PDF]
, 2007 . Bounded parameter Markov Decision Processes (BMDPs) address the issue of dealing with uncertainty in the parameters of a Markov Decision Process (MDP).
Tewari, Ambuj +3 more
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Optimal Intervention in Semi-Markov-Based Asynchronous Probabilistic Boolean Networks
Complexity, 2018 Synchronous probabilistic Boolean networks (PBNs) and generalized asynchronous PBNs have received significant attention over the past decade as a tool for modeling complex genetic regulatory networks.
Qiuli Liu +3 more
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