Depth-Bounded Fuzzy Simulations and Bisimulations between Fuzzy Automata

TL;DR

This paper introduces depth-bounded fuzzy simulations and bisimulations for fuzzy automata, providing polynomial-time algorithms for their computation and a logical characterization, addressing limitations of previous fuzzy behavioral comparison methods.

Contribution

It proposes a novel notion of depth-bounded fuzzy simulations and bisimulations, enabling approximate behavioral comparison with polynomial algorithms and a logical characterization.

Findings

Defines depth-bounded fuzzy simulations and bisimulations.

Provides polynomial-time algorithms for their computation.

Establishes a logical characterization with the Hennessy-Milner property.

Abstract

Simulations and bisimulations are well-established notions in crisp/fuzzy automata theory and are widely used to compare the behaviors of automata. Their main drawback is that they compare the behaviors of fuzzy automata in a crisp manner. Recently, fuzzy simulations and fuzzy bisimulations have been defined for fuzzy automata as a kind of approximate simulations and approximate bisimulations that compare the behaviors of fuzzy automata in a fuzzy manner. However, they still suffer from serious shortcomings. First, they still cannot correlate all fuzzy automata that are intuitively "more or less" (bi)similar. Second, the currently known algorithms for computing the greatest fuzzy simulation or bisimulation between two finite fuzzy automata have an exponential time complexity when the {\L}ukasiewicz or product structure of fuzzy values is used. This work deals with these problems, providing approximations of fuzzy simulations and fuzzy bisimulations. We define such approximations via a novel notion of decreasing sequences of fuzzy relations whose infima are, under some conditions, fuzzy simulations (respectively, bisimulations). We call such a sequence a depth-bounded fuzzy simulation (respectively, bisimulation), as the $n$th element from the sequence compares the behaviors of fuzzy automata, but only for words with a length bounded by $n$. We further provide a logical characterization of the greatest depth-bounded fuzzy simulation or bisimulation between two fuzzy automata by proving that it satisfies the corresponding Hennessy-Milner property. Finally, we provide polynomial-time algorithms for computing the $n$th component of the greatest depth-bounded fuzzy simulation (respectively, bisimulation) between two finite fuzzy automata.