Results 11 to 20 of about 73,852 (168)
Надежность и качество сложных систем, 2022 Background. In the conditions of modern military conflicts, the problem of effective control of large groups of robots is actualized. The large amount of data associated with the operation of robotic systems (RC) determines the existence of ...
S.V. Ivanov +3 more
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Markov processes follow from the principle of maximum caliber [PDF]
Journal of Chemical Physics, 2012 Steve Presse, Hao Ge, Kingshuk Ghosh
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Abstraction-Based Planning for Uncertainty-Aware Legged Navigation
IEEE Open Journal of Control Systems, 2023 This article addresses the problem of temporal-logic-based planning for bipedal robots in uncertain environments. We first propose an Interval Markov Decision Process abstraction of bipedal locomotion (IMDP-BL). Motion perturbations from multiple sources
Jesse Jiang, Samuel Coogan, Ye Zhao
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Implementing Markovian models for extendible Marshall–Olkin distributions
Dependence Modeling, 2022 We derive a novel stochastic representation of exchangeable Marshall–Olkin distributions based on their death-counting processes. We show that these processes are Markov.
Sloot Henrik
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Markov and Semi-Markov Chains, Processes, Systems, and Emerging Related Fields
Mathematics, 2021 Probability resembles the ancient Roman God Janus since, like Janus, probability also has a face with two different sides, which correspond to the metaphorical gateways and transitions between the past and the future [...]
P.-C.G. Vassiliou, Andreas C. Georgiou
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Markov Processes in Data Center Networks
IEEE Access, 2021 A data center network is an important infrastructure in various applications of modern information technologies. Data centers store files with useful information, but the lifetime of these data centers is limited.
Fan-Qi Ma, Rui-Na Fan
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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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Controlled Discrete-Time Semi-Markov Random Evolutions and Their Applications
Mathematics, 2021 In this paper, we introduced controlled discrete-time semi-Markov random evolutions. These processes are random evolutions of discrete-time semi-Markov processes where we consider a control. applied to the values of random evolution.
Anatoliy Swishchuk, Nikolaos Limnios
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A Continuous-Time Semi-Markov System Governed by Stepwise Transitions
Mathematics, 2022 In this paper, we introduce a class of stochastic processes in continuous time, called step semi-Markov processes. The main idea comes from bringing an additional insight to a classical semi-Markov process: the transition between two states is ...
Vlad Stefan Barbu +2 more
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Estimation and control using sampling-based Bayesian reinforcement learning
IET Cyber-Physical Systems, 2019 Real-world autonomous systems operate under uncertainty about both their pose and dynamics. Autonomous control systems must simultaneously perform estimation and control tasks to maintain robustness to changing dynamics or modelling errors.
Patrick Slade +3 more
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