Nondeterministic Fuzzy Simulation and Bisimulation

Deng, Hui; Li, Zhi

doi:10.1049/cje.2020.01.007

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…Because of symmetry, trace(X 1 ) ⊇ trace(X 2 ), hence trace(X 1 ) = trace(X 2 ). The proof train of thought of the above theorems and lemmas, we refer to the proofs in fondeterministic fuzzy bisimulation [17]. The labeling function is:…”

Section: B Possibilistic Cost Bisimulationmentioning

confidence: 99%

Possibilistic Cost Computation Tree Logic and Related Equivalence, Abstraction Technique

Deng

Zhang²,

Huang³

2023

IEEE Access

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Recently, probabilistic Kripke structures have been used to represent uncertain systems; nevertheless, important transition costs were ignored in earlier studies, making it impossible to model some uncertain systems with costs. To compensate for the major shortcoming, this research addresses the transition costs suggested in uncertain systems. First of all, we offer possibilistic Kripke cost structures and associated possibilistic costs such as cumulative cost and possibilistic expected cost. As the verification model, furthermore, we investigated the syntax and semantics of possibilistic cost computation tree logic and utilized them to develop verification characteristics of possibilistic Kripke cost structures. Finally, as solutions to the state space explosion problem of possibilistic cost computation tree logic model checking, abstraction and equivalence are presented as methods to reduce the state numbers and frameworks of possibilistic Kripke cost structures.

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Section: B Possibilistic Cost Bisimulationmentioning

confidence: 99%

Possibilistic Cost Computation Tree Logic and Related Equivalence, Abstraction Technique

Deng

Zhang²,

Huang³

2023

IEEE Access

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“…These model structures find applicability across a spectrum of complex domains, encompassing strategic decision-making, cancer metabolism investigation, security protocol verification, artificial intelligence analysis, robotics advancements, control systems optimization, and various other fields [15][16][17][18] . Particularly salient is the role of nondeterministic fuzzy Kripke structures in addressing the complexities inherent to real-world situations marked by uncertainty 19,20 . These structures amalgamate multiple fuzzy variables and embrace the integration of nondeterministic actions, thus affording them an augmented capacity for comprehensive expression of uncertainty and variability.…”

Section: Introductionmentioning

confidence: 99%

Theoretical foundations, computational methods, and practical applications of nondeterministic fuzzy abstraction

Deng

2023

Preprint

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Efficient and effective modeling of complex real-world situations characterized by uncertainty poses a substantial challenge. This study addresses this challenge by introducing a nondeterministic fuzzy abstraction approach to enhance efficiency and effectiveness in this context. The theoretical framework establishes a standardized representation of nondeterministic fuzzy Kripke structures, accompanied by definitions associated with nondeterministic fuzzy abstraction. The methods section presents an algorithm for realizing nondeterministic fuzzy abstraction, and it is well-suited for practical implementation in computer programs. The results section demonstrates the practical application of the proposed approach by modeling the process of treating a patient with ulcers in the terminal ileum. In the discussion section, a comparative study of nondeterministic fuzzy abstraction underscores its broad applicability and compatibility across various uncertainty and certainty model structures.

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$$\epsilon $$-Approximate Bisimulations for Nondeterministic Fuzzy Kripke Structures

Liu

2023

Communications in Computer and Information Science

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Nondeterministic Fuzzy Simulation and Bisimulation

Cited by 3 publications

References 11 publications

Possibilistic Cost Computation Tree Logic and Related Equivalence, Abstraction Technique

Possibilistic Cost Computation Tree Logic and Related Equivalence, Abstraction Technique

Theoretical foundations, computational methods, and practical applications of nondeterministic fuzzy abstraction

$$\epsilon $$-Approximate Bisimulations for Nondeterministic Fuzzy Kripke Structures

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