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Simulations and bisimulations between two fuzzy automata over a complete residuated lattice were defined by \'Ciri\'c et al. (2012) as fuzzy relations between the sets of states of the automata. However, they act as a crisp relationship…

Formal Languages and Automata Theory · Computer Science 2022-05-05 Linh Anh Nguyen

Recently, two types of simulations (forward and backward simulations) and four types of bisimulations (forward, backward, forward-backward, and backward-forward bisimulations) between fuzzy automata have been introduced. If there is at…

Formal Languages and Automata Theory · Computer Science 2014-04-01 Miroslav Ćirić , Jelena Ignjatović , Ivana Jančić , Nada Damljanović

Bisimulations have been widely used in many areas of computer science to model equivalence between various systems, and to reduce the number of states of these systems, whereas uniform fuzzy relations have recently been introduced as a…

Formal Languages and Automata Theory · Computer Science 2011-05-09 Miroslav Ćirić , Jelena Ignjatović , Nada Damljanović , Milan Bašić

There has been a long history of using fuzzy language equivalence to compare the behavior of fuzzy systems, but the comparison at this level is too coarse. Recently, a finer behavioral measure, bisimulation, has been introduced to fuzzy…

Artificial Intelligence · Computer Science 2016-11-15 Yongzhi Cao , Guoqing Chen , Etienne Kerre

Like bisimulations, simulations and directed simulations are used for analyzing graph-based structures such as automata, labeled transition systems, linked data networks, Kripke models and interpretations in description logic. Simulations…

Data Structures and Algorithms · Computer Science 2020-12-04 Linh Anh Nguyen

There are two kinds of bisimulation, namely crisp and fuzzy, between fuzzy structures such as fuzzy automata, fuzzy labeled transition systems, fuzzy Kripke models and fuzzy interpretations in description logics. Fuzzy bisimulations between…

Logic in Computer Science · Computer Science 2021-06-16 Linh Anh Nguyen

Fuzzy graph-based structures such as fuzzy automata, fuzzy labeled transition systems, fuzzy Kripke models, fuzzy social networks and fuzzy interpretations in fuzzy description logics are useful in various applications. Given two states,…

Data Structures and Algorithms · Computer Science 2021-07-20 Linh Anh Nguyen

Fuzzy structures such as fuzzy automata, fuzzy transition systems, weighted social networks and fuzzy interpretations in fuzzy description logics have been widely studied. For such structures, bisimulation is a natural notion for…

Data Structures and Algorithms · Computer Science 2023-06-02 Linh Anh Nguyen , Dat Xuan Tran

In a recent paper, we have introduced two types of fuzzy simulations (forward and backward) and five types of fuzzy bisimulations (forward, backward, forward-backward, backward-forward and regular) between Kripke models for the fuzzy…

Logic · Mathematics 2025-02-17 Marko Stanković , Miroslav Ćirić , Jelena Ignjatović

We formulate and prove logical characterizations of crisp simulations and crisp directed simulations between fuzzy labeled transition systems with respect to fuzzy modal logics that use a general t-norm-based semantics. The considered…

Logic in Computer Science · Computer Science 2021-09-07 Linh Anh Nguyen , Ngoc-Thanh Nguyen

In this paper we study the equivalence of nondeterministic automata pairing the concept of a bisimulation with the recently introduced concept of a uniform relation. In this symbiosis, uniform relations serve as equivalence relations which…

Formal Languages and Automata Theory · Computer Science 2011-03-01 Miroslav Ćirić , Jelena Ignjatović , Milan Bašić , Ivana Jančić

Fuzzy relational identification builds a relational model describing systems behaviour by a nonlinear mapping between its variables. In this paper, we propose a new fuzzy relational algorithm based on simplified max-min relational equation.…

Robotics · Computer Science 2007-05-23 P. J. Costa Branco , J. A. Dente

Description logics (DLs) are a suitable formalism for representing knowledge about domains in which objects are described not only by attributes but also by binary relations between objects. Fuzzy extensions of DLs can be used for such…

Logic in Computer Science · Computer Science 2020-08-10 Linh Anh Nguyen , Quang-Thuy Ha , Ngoc Thanh Nguyen , Thi Hong Khanh Nguyen , Thanh-Luong Tran

The problem of minimizing finite fuzzy interpretations in fuzzy description logics (FDLs) is worth studying. For example, the structure of a fuzzy/weighted social network can be treated as a fuzzy interpretation in FDLs, where actors are…

Artificial Intelligence · Computer Science 2023-03-22 Linh Anh Nguyen

Behaviour distances to measure the resemblance of two states in a (nondeterministic) fuzzy transition system have been proposed recently in the literature. Such a distance, defined as a pseudo-ultrametric over the state space of the model,…

Logic in Computer Science · Computer Science 2017-01-25 Taolue Chen , Tingting Han , Yongzhi Cao

Hybrid automata are a natural framework for modeling and analyzing systems which exhibit a mixed discrete continuous behaviour. However, the standard operational semantics defined over such models implicitly assume perfect knowledge of the…

Systems and Control · Computer Science 2013-08-27 Alberto Casagrande , Tommaso Dreossi , Carla Piazza

Determinization of fuzzy finite automata is understood here as a procedure of their conversion into equivalent crisp-deterministic fuzzy automata, which can be viewed as being deterministic with possibly infinitely many states, but with…

Formal Languages and Automata Theory · Computer Science 2014-12-17 Ivana Micić , Zorana Jančić , Jelena Ignjatović , Miroslav Ćirić

Higher-dimensional automata (HDAs) are models of non-interleaving concurrency for analyzing concurrent systems. There is a rich literature that deals with bisimulations for concurrent systems, and some of them have been extended to HDAs.…

Logic in Computer Science · Computer Science 2026-03-03 Safa Zouari , Krzysztof Ziemiański , Uli Fahrenberg

Fuzzy modeling has many advantages over the non-fuzzy methods, such as robustness against uncertainties and less sensitivity to the varying dynamics of nonlinear systems. Data-driven fuzzy modeling needs to extract fuzzy rules from the…

Systems and Control · Computer Science 2018-06-08 Erick de la Rosa , Wen Yu

We re-examine a practical aspect of combinatorial fuzzy problems of various types, including search, counting, optimization, and decision problems. We are focused only on those fuzzy problems that take series of fuzzy input objects and…

Artificial Intelligence · Computer Science 2016-11-17 Tomoyuki Yamakami
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