18 results with keyword: 'reachability in continuous time markov reward decision processes'
As a corollary, ǫ -optimal schedulers for reward reachability objectives in uniform CT- MDPs can be obtained in polynomial time using a simple backward greedy algorithm....
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This paper solves the problem of computing the maximum and mini- mum probability to reach a set of goal states within a given time bound for locally uniform continuous-time
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This paper presents an efficient algorithm to compute the maxi- mum (or minimum) probability to reach a set of goal states within a given time bound in a uniform CTMDP, i.e., a CTMDP
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Adaptive aggregation for reinforcement learning in average reward markov decision processes. Continuous
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We reported that histamine inhibition of serum- activated zymosan-induced lysosomal enzyme release from granulocytes is an H2 receptor response and parallels increases in
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This is based on a novel algorithm using Gaussian Processes (GPs) and statistical model checking to sample in an unbiased manner the gradient of the functional associating
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Finally, for the constrained models with the total expected cost, we present in Section 4 the sufficient class of realizable strategies, that is, Poisson-related strategies, and show
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Keywords Model Checking, Stochastic Petri nets, Rewards, Continuous-time Markov Chains, Markov Reward Models, Interval Decision Diagrams, Multi-threading, Con- tinuous Stochastic
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Our molds are manufactured using pure silicon rubber, and are microsoft visual c 2005 redistributable x64 download designed to cure "soft" so that removing frozen cakes or
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The model we present is consistent with the second explanation. The negative shift in labor supply increases the relative abundance of capital and generates an incentive for
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Semi-Markov decision processes pro- vide a more permissive model than continuous-time Markov decision processes, since they allow as residence-time distributions any
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By defining pseudo-variance, the deviation of the deterministic stationary policy f and the Poisson equation, a series of con- cepts and theorems, we prove the existence of
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Learning optimal policies via stochastic functional gradient ascent In this section we give a variational formulation of the control problem of determining the optimal scheduler
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The present paper considers the constrained optimal control problem with total undiscounted criteria for a continuous-time Markov decision process (CTMDP) in Borel state and
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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
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– Under a weak condition, e.g., in the discounted case, for any control strat- egy, there is an equivalent Markov randomized strategy (Theorem 1) and an equivalent mixture of
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Social security for information we ve noticed some unusual activity outlook account related email will need to personalize your account, you know the account.. For you to have
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