Xia Li¹, Zhanyou Ma^1,*, Zhibao Mian², Ziyuan Liu¹, Ruiqi Huang¹, Nana He¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4129-4152, 2024, DOI:10.32604/cmc.2024.047168

Abstract Model checking is an automated formal verification method to verify whether epistemic multi-agent systems adhere to property specifications. Although there is an extensive literature on qualitative properties such as safety and liveness, there is still a lack of quantitative and uncertain property verifications for these systems. In uncertain environments, agents must make judicious decisions based on subjective epistemic. To verify epistemic and measurable properties in multi-agent systems, this paper extends fuzzy computation tree logic by introducing epistemic modalities and proposing a new Fuzzy Computation Tree Logic of Knowledge (FCTLK). We represent fuzzy multi-agent systems as distributed knowledge bases with fuzzy… More >

Ling Ding¹, Hongyan Wan^2,*, Luokai Hu¹, Yu Chen¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2655-2670, 2023, DOI:10.32604/cmc.2023.035542

Abstract Product detection based on state abstraction technologies in the software product line (SPL) is more complex when compared to a single system. This variability constitutes a new complexity, and the counterexample may be valid for some products but spurious for others. In this paper, we found that spurious products are primarily due to the failure states, which correspond to the spurious counterexamples. The violated products correspond to the real counterexamples. Hence, identifying counterexamples is a critical problem in detecting violated products. In our approach, we obtain the violated products through the genuine counterexamples, which have no failure state, to avoid… More >

Honghao Gao^{1, 2, 5}, Wanqiu Huang^{1, 4}, Xiaoxian Yang³

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 547-559, 2019, DOI:10.31209/2019.100000110

Abstract Path planning is an important topic of research in modern intelligent traffic systems (ITSs). Traditional path planning methods aim to identify the shortest path and recommend this path to the user. However, the shortest path is not always optimal, especially in emergency rescue scenarios. Thus, complex and changeable factors, such as traffic congestion, road construction and traffic accidents, should be considered when planning paths. To address this consideration, the maximum passing probability of a road is considered the optimal condition for path recommendation. In this paper, the traffic network is abstracted as a directed graph. Probabilistic data on traffic flow… More >