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Wuniu LIU, Junmei WANG, Qing HE, et al., “Model Checking Computation Tree Logic over Multi-valued Decision Processes and Its Reduction Techniques,” Chinese Journal of Electronics, vol. x, no. x, pp. 1–13, xxxx doi: 10.23919/cje.2021.00.333
Citation: Wuniu LIU, Junmei WANG, Qing HE, et al., “Model Checking Computation Tree Logic over Multi-valued Decision Processes and Its Reduction Techniques,” Chinese Journal of Electronics, vol. x, no. x, pp. 1–13, xxxx doi: 10.23919/cje.2021.00.333

Model Checking Computation Tree Logic over Multi-valued Decision Processes and Its Reduction Techniques

doi: 10.23919/cje.2021.00.333
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  • Author Bio:

    Wuniu LIU was born in Yulin, Shaanxi, China, in 1997. He received the M.Sc. degree in computer science and technology in 2022 from the School of Computer Science, Shaanxi Normal University, Xi’an, China, where he is currently working toward the doctoral degree in applied mathematics from the School of Mathematics and Statistics. He has published some papers in academic journals such as IEEE Transactions on Systems, Man, and Cybernetics: Systems, IEEE Transactions on Emerging Topics in Computational Intelligence and IEEE Transactions Fuzzy Systems. His research interests include computational intelligence, fuzzy logic, control theory and quantum computation. (Email: liuwuniu@snnu.edu.cn)

    Junmei WANG was born in 1995. She received the master’s degree from the School of Computer Science of Shaanxi Normal University, in 2022. She is now a researcher at Xi'an BYD Auto Company Limited. Her research interests include formal methods, model checking. (Email: wangjunmei@snnu.edu.cn)

    Qing HE was born in Xi’an, Shaanxi, China, in 1998. She received the B.S. degree in computer science and technology in 2020 from the School of Computer Science, Shaanxi Normal University, Xi’an, China, where she is currently working toward the doctoral degree in computer science and technology with the School of Computer Science. Her research interests include model checking and fuzzy temporal logic. (Email: heqing@snnu.edu.cn)

    Yongming LI received the Ph.D. degree in mathematics from Sichuan University, Chengdu, China, in 1996. He is currently with Shaanxi Normal University, Xi'an, China, as a Professor of mathematics and computer science. He authored or coauthored more than 300 journal articles in several IEEE Transactions and other high impact journals. He serves as a member of fuzzy systems technical committee in IEEE Computational Intelligence Society, deputy director of the Fuzzy Mathematics and Fuzzy Systems Committee of the Chinese Society for Systems Engineering, vice chairman of the Intelligent Computing Society of the National Operational Research Society, vice chairman of the Computer Education Committee of the National Normal University, director of the Theoretical Computer Society of the Chinese Computer Society, executive director of the Shaanxi Computer Society, and executive committee member of the CCF (Chinese Computer Society) Xi'an branch. His research interests include model checking, fuzzy control theory, fuzzy automata theory, spatial reasoning, quantum logic and quantum computation, and topology over lattices. (Email: liyongm@snnu.edu.cn)

  • Corresponding author: Email: liyongm@snnu.edu.cn
  • Received Date: 2021-09-06
  • Accepted Date: 2023-12-08
  • Available Online: 2024-02-02
  • Model checking computation tree logic (CTL) based on multi-valued possibility measures has been studied by Li et al. in 2019. However, the previous work did not consider the nondeterministic choices inherent in systems represented by multi-valued Kripke structures (MvKSs). This nondeterminism is crucial for accurate system modeling, decision making, and control capabilities. To address this limitation, we draw inspiration from the generalization of Markov chains (MCs) to Markov decision processes (MDPs) in probabilistic systems. By integrating nondeterminism into MvKS, we introduce multi-valued decision processes (MvDPs) as a framework for modeling MvKSs with nondeterministic choices. Additionally, we investigate the challenges of model checking over MvDPs. In our approach, verifying properties are expressed by using multi-valued computation tree logic (MvCTL) based on schedulers. Our primary objective is to leverage fixpoint techniques to determine the maximum and minimum possibilities of the system satisfying temporal properties. This allows us to identify the optimal or worst-case schedulers for decision making or control purposes. Furthermore, we aim to develop reduction techniques that enhance the efficiency of model checking, thereby reducing the associated time complexity.
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