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Autori principali: Avila, Daniel, Junca, Mauricio
Natura: Preprint
Pubblicazione: 2018
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Accesso online:https://arxiv.org/abs/1806.00052
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author Avila, Daniel
Junca, Mauricio
author_facet Avila, Daniel
Junca, Mauricio
contents We consider a Markov control model in discrete time with countable both state space and action space. Using the value function of a suitable long-run average reward problem, we study various reachability/controllability problems. First, we characterize the domain of attraction and escape set of the system, and a generalization called $p$-domain of attraction, using the aforementioned value function. Next, we solve the problem of maximizing the probability of reaching a set $A$ while avoiding a set $B$. Finally, we consider a constrained version of the previous problem where we ask for the probability of reaching the set $B$ to be bounded. In the finite case, we use linear programming formulations to solve these problems. Finally, we apply our results to a example of an object that navigates under stochastic influence.
format Preprint
id arxiv_https___arxiv_org_abs_1806_00052
institution arXiv
publishDate 2018
record_format arxiv
spellingShingle On reachability of Markov chains: A long-run average approach
Avila, Daniel
Junca, Mauricio
Optimization and Control
We consider a Markov control model in discrete time with countable both state space and action space. Using the value function of a suitable long-run average reward problem, we study various reachability/controllability problems. First, we characterize the domain of attraction and escape set of the system, and a generalization called $p$-domain of attraction, using the aforementioned value function. Next, we solve the problem of maximizing the probability of reaching a set $A$ while avoiding a set $B$. Finally, we consider a constrained version of the previous problem where we ask for the probability of reaching the set $B$ to be bounded. In the finite case, we use linear programming formulations to solve these problems. Finally, we apply our results to a example of an object that navigates under stochastic influence.
title On reachability of Markov chains: A long-run average approach
topic Optimization and Control
url https://arxiv.org/abs/1806.00052