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Variations on the Stochastic Shortest Path Problem

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Article , Preprint , Conference object 01 Jan 2015Embargo end date: 01 Jan 2014 France, France, Belgium Publisher:Springer Berlin HeidelbergFunded by:EC | CASSTING, EC | INVEST

Authors: Randour, Mickael; Raskin, Jean-François; Sankur, Ocan;

doi: 10.1007/978-3-662-46081-8_1 , 10.48550/arxiv.1411.0835

arXiv: http://arxiv.org/abs/1411.0835

handle: 2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/186910

Variations on the Stochastic Shortest Path Problem

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Abstract

In this invited contribution, we revisit the stochastic shortest path problem, and show how recent results allow one to improve over the classical solutions: we present algorithms to synthesize strategies with multiple guarantees on the distribution of the length of paths reaching a given target, rather than simply minimizing its expected value. The concepts and algorithms that we propose here are applications of more general results that have been obtained recently for Markov decision processes and that are described in a series of recent papers.

Invited paper for VMCAI 2015

Countries

France, France, Belgium

Related Organizations

French National Centre for Scientific Research
France
French Institute for Research in Computer Science and Automation
France
University of Rennes 1
France
École normale supérieure de Cachan
France
Université de Rennes 1
France

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Keywords

FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Informatique générale, Formal Languages and Automata Theory (cs.FL), Computer Science - Formal Languages and Automata Theory, Logic in Computer Science (cs.LO), Computer Science - Computer Science and Game Theory, Optimization and Control (math.OC), Informatique mathématique, FOS: Mathematics, Mathematics - Optimization and Control, [INFO.INFO-FL] Computer Science [cs]/Formal Languages and Automata Theory [cs.FL], Computer Science and Game Theory (cs.GT)

Impact byBIP!

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	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%