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https://doi.org/10.1109/time.2...
Article . 2007 . Peer-reviewed
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On the Equivalence of Automaton-Based Representations of Time Granularities

Authors: DAL LAGO Ugo; MONTANARI, Angelo; PUPPIS, Gabriele;

On the Equivalence of Automaton-Based Representations of Time Granularities

Abstract

A time granularity can be viewed as the partitioning of a temporal domain in groups of elements, where each group is perceived as an indivisible unit. In this paper we explore an automaton-based approach to the management of time granularity that compactly represents time granularities as single-string automata with counters, that is, Buchi automata, extended with counters, that accept a single infinite word. We focus our attention on the equivalence problem for the class of restricted labeled single-string automata (RLA for short). The equivalence problem for RLA is the problem of establishing whether two given RLA represent the same time granularity. The main contribution of the paper is the reduction of the (non-)equivalence problem for RLA to the satisfiability problem for linear diophantine equations with bounds on variables. Since the latter problem has been shown to be NP-complete, we have that the RLA equivalence problem is in co-NP.

Country
Italy
Keywords

time granularity; automata, GRANULARITÀ TEMPORALI; AUTOMI

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Average
Average
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