Results 11 to 20 of about 26,957 (159)
Synchronizing Objectives for Markov Decision Processes [PDF]
Electronic Proceedings in Theoretical Computer Science, 2011 We introduce synchronizing objectives for Markov decision processes (MDP). Intuitively, a synchronizing objective requires that eventually, at every step there is a state which concentrates almost all the probability mass.
Mahsa Shirmohammadi +2 more
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A Weighted Markov Decision Process [PDF]
Operations Research, 1992 The two most commonly considered reward criteria for Markov decision processes are the discounted reward and the long-term average reward. The first tends to “neglect” the future, concentrating on the short-term rewards, while the second one tends to do the opposite.
Krass, D, Filar, JA, Sinha, SS
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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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Learning Markov Decision Processes for Model Checking [PDF]
Electronic Proceedings in Theoretical Computer Science, 2012 Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system ...
Hua Mao +5 more
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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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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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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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