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ω-automaton

About: ω-automaton is a research topic. Over the lifetime, 2299 publications have been published within this topic receiving 68468 citations. The topic is also known as: stream automaton & ω-automata.


Papers
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Journal ArticleDOI
TL;DR: It is shown that there are cases when all previous methods result in infinite automata, while Brzozowski type determinization results in a finite one, as in the case of ordinary nondeterministic automata.

23 citations

Book ChapterDOI
11 Oct 2004
TL;DR: In the setting of identification in the limit with probability one, it is proved that stochastic deterministic finite automata cannot be identified from only a polynomial quantity of data.
Abstract: Stochastic deterministic finite automata have been introduced and are used in a variety of settings. We report here a number of results concerning the learnability of these finite state machines. In the setting of identification in the limit with probability one, we prove that stochastic deterministic finite automata cannot be identified from only a polynomial quantity of data. If concerned with approximation results, they become Pac-learnable if the L ∞ norm is used. We also investigate queries that are sufficient for the class to be learnable.

23 citations

Journal ArticleDOI
TL;DR: In this article, the authors focus on generalizations of QFAs where the input head operates in one-way or real-time mode, and present some new results regarding their superiority over their classical counterparts.
Abstract: In automata theory, quantum computation has been widely examined for finite state machines, known as quantum finite automata (QFAs), and less attention has been given to QFAs augmented with counters or stacks. In this paper, we focus on such generalizations of QFAs where the input head operates in one-way or realtime mode, and present some new results regarding their superiority over their classical counterparts. Our first result is about the nondeterministic acceptance mode: Each quantum model architecturally intermediate between realtime finite state automaton and one-way pushdown automaton (one-way finite automaton, realtime and one-way finite automata with one-counter, and realtime pushdown automaton) is superior to its classical counterpart. The second and third results are about bounded error language recognition: for any k > 0, QFAs with k blind counters outperform their deterministic counterparts; and, a one-way QFA with a single head recognizes an infinite family of languages, which can be recognized by one-way probabilistic finite automata with at least two heads. Lastly, we compare the nondeterminictic and deterministic acceptance modes for classical finite automata with k blind counter(s), and we show that for any k > 0, the nondeterministic models outperform the deterministic ones.

23 citations

Book ChapterDOI
17 Aug 2006
TL;DR: It is shown that the existing definition can indeed be used for minimization and give an algorithm that computes the delayed-simulation relation and implemented the two algorithms and report on experimental results.
Abstract: We consider the problem of minimization of generalized Buchi automata. We extend fair-simulation minimization and delayed-simulation minimization to the case where the Buchi automaton has multiple acceptance conditions. For fair simulation, we show how to efficiently compute the fair-simulation relation while maintaining the structure of the automaton. We then use the fair-simulation relation to merge states and remove transitions. Our fair-simulation algorithm works in time O(mn3k2) where m is the number of transitions, n is the number of states, and k is the number of acceptance sets. For delayed simulation, we extend the existing definition to the case of multiple acceptance conditions. We show that our definition can indeed be used for minimization and give an algorithm that computes the delayed-simulation relation. Our delayed-simulation algorithm works in time O(mn3k). We implemented the two algorithms and report on experimental results.

23 citations

Book ChapterDOI
02 Oct 2005
TL;DR: In this paper, the authors present techniques that allow the method to be applied to more complex pre-interpretations and larger programs, and demonstrate through experiments that much more complex analyses become feasible.
Abstract: Any finite tree automaton (or regular type) can be used to construct an abstract interpretation of a logic program, by first determinising and completing the automaton to get a pre-interpretation of the language of the program. This has been shown to be a flexible and practical approach to building a variety of analyses, both generic (such as mode analysis) and program-specific (with respect to a type describing some particular property of interest). Previous work demonstrated the approach using pre-interpretations over small domains. In this paper we present techniques that allow the method to be applied to more complex pre-interpretations and larger programs. There are two main techniques presented: the first is a novel algorithm for determinising finite tree automata, yielding a compact “product” form of the transitions of the result automaton, that is often orders of magnitude smaller than an explicit representation of the automaton. Secondly, it is shown how this form (which is a representation of a pre-interpretation) can then be input directly to a BDD-based analyser of Datalog programs. We demonstrate through experiments that much more complex analyses become feasible.

23 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20238
202219
20201
20191
20185
201748