Discounted Markov Decision Processes with Constrained Costs: the decomposition approach [PDF]
E3S Web of Conferences, 2021 In this paper we consider a constrained optimization of discrete time Markov Decision Processes (MDPs) with finite state and action spaces, which accumulate both a reward and costs at each decision epoch.
Semmouri Abdellatif +2 more
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Multi-Objective Model Checking of Markov Decision Processes [PDF]
Logical Methods in Computer Science, 2008 We study and provide efficient algorithms for multi-objective model checking problems for Markov Decision Processes (MDPs). Given an MDP, M, and given multiple linear-time (\omega -regular or LTL) properties \varphi\_i, and probabilities r\_i \epsilon [0,
Kousha Etessami +3 more
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Multi-weighted Markov Decision Processes with Reachability Objectives [PDF]
Electronic Proceedings in Theoretical Computer Science, 2018 In this paper, we are interested in the synthesis of schedulers in double-weighted Markov decision processes, which satisfy both a percentile constraint over a weighted reachability condition, and a quantitative constraint on the expected value of a ...
Patricia Bouyer +3 more
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Debugging of Markov Decision Processes (MDPs) Models [PDF]
Electronic Proceedings in Theoretical Computer Science, 2016 In model checking, a counterexample is considered as a valuable tool for debugging. In Probabilistic Model Checking (PMC), counterexample generation has a quantitative aspect. The counterexample in PMC is a set of paths in which a path formula holds, and
Hichem Debbi
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Of Cores: A Partial-Exploration Framework for Markov Decision Processes [PDF]
Logical Methods in Computer Science, 2020 We introduce a framework for approximate analysis of Markov decision processes (MDP) with bounded-, unbounded-, and infinite-horizon properties. The main idea is to identify a "core" of an MDP, i.e., a subsystem where we provably remain with high ...
Jan Křetínský, Tobias Meggendorfer
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Performance evaluation, optimization and dynamic decision in blockchain systems: a recent overview [PDF]
Blockchain, 2023 With rapid development of blockchain technology as well as integration of various application areas, performance evaluation, performance optimization, and dynamic decision in blockchain systems are playing an increasingly important role in developing new
Quan-Lin Li, Yan-Xia Chang, Qing Wang
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Framework for solving time-delayed Markov Decision Processes
Physical Review Research, 2023 Reinforcement learning has revolutionized our understanding of evolved systems and our ability to engineer systems based on a theoretical framework for understanding how to maximize expected reward. However, time delays between the observation and action
Yorgo Sawaya +2 more
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Finite State Approximations for Countable State Infinite Horizon Discounted Markov Decision Processes [PDF]
Modeling, Identification and Control, 1987 It is proved that the optimal policy of a Markov decision process where the state space is truncated, will approximate the policy in case of no truncation.
Sjur D. Flåm
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Deterministic Discounted Markov Decision Processes with Fuzzy Rewards/Costs
Fuzzy Information and Engineering, 2023 The article concerns a study of infinite-horizon deterministic Markov decision processes (MDPs) for which the fuzzy environment will be presented through considering these MDPs with both fuzzy rewards and fuzzy costs.
Hugo Cruz-Suárez +2 more
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Markov Decision Processes with Multiple Long-run Average Objectives [PDF]
Logical Methods in Computer Science, 2014 We study Markov decision processes (MDPs) with multiple limit-average (or mean-payoff) functions. We consider two different objectives, namely, expectation and satisfaction objectives.
Tomáš Brázdil +4 more
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