Results 1 to 10 of about 120,210 (259)
Optimal Time-Abstract Schedulers for CTMDPs and Markov Games [PDF]
Electronic Proceedings in Theoretical Computer Science, 2010 We study time-bounded reachability in continuous-time Markov decision processes for time-abstract scheduler classes. Such reachability problems play a paramount role in dependability analysis and the modelling of manufacturing and queueing systems ...
Markus Rabe, Sven Schewe
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Q-LVS: A Q-Learning-based Algorithm for Video Streaming in Peer-to-Peer Networks Considering a Token-Based Incentive Mechanism [PDF]
Journal of Artificial Intelligence and Data Mining, 2022 Peer-to-peer video streaming has reached great attention during recent years. Video streaming in peer-to-peer networks is a good way to stream video on the Internet due to the high scalability, high video quality, and low bandwidth requirements.
Z. Imanimehr
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Discrete Dynamics in Nature and Society, 2022 This paper is concerned with the asymptotic optimality of quantized stationary policies for continuous-time Markov decision processes (CTMDPs) in Polish spaces with state-dependent discount factors, where the transition rates and reward rates are allowed
Xiao Wu, Yanqiu Tang
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Mathematics, 2021 This paper is aimed at developing a stochastic volatility model that is useful to explain the dynamics of the returns of gold, silver, and platinum during the period 1994–2019.
Martha Carpinteyro +2 more
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Effects of Sampling and Prediction Horizon in Reinforcement Learning
IEEE Access, 2021 Plain reinforcement learning (RL) may be prone to loss of convergence, constraint violation, unexpected performance, etc. Commonly, RL agents undergo extensive learning stages to achieve proper functionality.
Pavel Osinenko, Dmitrii Dobriborsci
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A Dynamic Programming Algorithm for Finding an Optimal Sequence of Informative Measurements
Entropy, 2023 An informative measurement is the most efficient way to gain information about an unknown state. We present a first-principles derivation of a general-purpose dynamic programming algorithm that returns an optimal sequence of informative measurements by ...
Peter N. Loxley, Ka-Wai Cheung
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Quasi-Deterministic Processes with Monotonic Trajectories and Unsupervised Machine Learning
Mathematics, 2021 This paper aims to consider approximation-estimation tests for decision-making by machine-learning methods, and integral-estimation tests are defined, which is a generalization for the continuous case.
Andrey V. Orekhov
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ეკონომიკური პროფილი, 2022 Artificial intelligence methods and technologies are increasingly included in human's everyday life. Managing actors in the context of their activities, from the planning stage to the decision-making stage, are faced with the need to operate with big ...
Gocha Ugulava
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PLoS Computational Biology, 2020 Recent high-dimensional single-cell technologies such as mass cytometry are enabling time series experiments to monitor the temporal evolution of cell state distributions and to identify dynamically important cell states, such as fate decision states in ...
Jake P Taylor-King +3 more
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Energies, 2022 Oil tanker disasters have been a cause of major environmental disasters, with multi-generational impacts. One of the greatest hazards is damage to the propulsion system that causes the ship to turn sideways to a wave and lose stability, which in storm ...
Zbigniew Łosiewicz +4 more
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