Probabilistic automata of bounded ambiguity

Probabilistic automata are a computational model introduced by Michael Rabin, extending nondeterministic finite automata with probabilistic transitions. Despite its simplicity, this model is very expressive and many of the associated algorithmic questions are undecidable. In this work we focus on th...

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Main Authors: Fijalkow, N, Riveros, C, Worrell, J
Format: Conference item
Published: Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2017
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author Fijalkow, N
Riveros, C
Worrell, J
author_facet Fijalkow, N
Riveros, C
Worrell, J
author_sort Fijalkow, N
collection OXFORD
description Probabilistic automata are a computational model introduced by Michael Rabin, extending nondeterministic finite automata with probabilistic transitions. Despite its simplicity, this model is very expressive and many of the associated algorithmic questions are undecidable. In this work we focus on the emptiness problem, which asks whether a given probabilistic automaton accepts some word with probability higher than a given threshold. We consider a natural and well-studied structural restriction on automata, namely the degree of ambiguity, which is defined as the maximum number of accepting runs over all words. We observe that undecidability of the emptiness problem requires infinite ambiguity and so we focus on the case of finitely ambiguous probabilistic automata. Our main results are to construct efficient algorithms for analysing finitely ambiguous probabilistic automata through a reduction to a multi-objective optimisation problem, called the stochastic path problem. We obtain a polynomial time algorithm for approximating the value of finitely ambiguous probabilistic automata and a quasi-polynomial time algorithm for the emptiness problem for 2-ambiguous probabilistic automata.
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spelling oxford-uuid:12f0021c-7bae-4f21-a7a2-8e0d060712842022-03-26T10:10:53ZProbabilistic automata of bounded ambiguityConference itemhttp://purl.org/coar/resource_type/c_5794uuid:12f0021c-7bae-4f21-a7a2-8e0d06071284Symplectic Elements at OxfordSchloss Dagstuhl - Leibniz-Zentrum für Informatik2017Fijalkow, NRiveros, CWorrell, JProbabilistic automata are a computational model introduced by Michael Rabin, extending nondeterministic finite automata with probabilistic transitions. Despite its simplicity, this model is very expressive and many of the associated algorithmic questions are undecidable. In this work we focus on the emptiness problem, which asks whether a given probabilistic automaton accepts some word with probability higher than a given threshold. We consider a natural and well-studied structural restriction on automata, namely the degree of ambiguity, which is defined as the maximum number of accepting runs over all words. We observe that undecidability of the emptiness problem requires infinite ambiguity and so we focus on the case of finitely ambiguous probabilistic automata. Our main results are to construct efficient algorithms for analysing finitely ambiguous probabilistic automata through a reduction to a multi-objective optimisation problem, called the stochastic path problem. We obtain a polynomial time algorithm for approximating the value of finitely ambiguous probabilistic automata and a quasi-polynomial time algorithm for the emptiness problem for 2-ambiguous probabilistic automata.
spellingShingle Fijalkow, N
Riveros, C
Worrell, J
Probabilistic automata of bounded ambiguity
title Probabilistic automata of bounded ambiguity
title_full Probabilistic automata of bounded ambiguity
title_fullStr Probabilistic automata of bounded ambiguity
title_full_unstemmed Probabilistic automata of bounded ambiguity
title_short Probabilistic automata of bounded ambiguity
title_sort probabilistic automata of bounded ambiguity
work_keys_str_mv AT fijalkown probabilisticautomataofboundedambiguity
AT riverosc probabilisticautomataofboundedambiguity
AT worrellj probabilisticautomataofboundedambiguity