Computation Tree Logic Model Checking of Multi-Agent Systems Based on Fuzzy Epistemic Interpreted Systems

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 epistemic interpreted systems. In addition, we provide a transformation algorithm from fuzzy epistemic interpreted systems to fuzzy Kripke structures, as well as transformation rules from FCTLK formulas to Fuzzy Computation Tree Logic (FCTL) formulas. Accordingly, we transform the FCTLK model checking problem into the FCTL model checking. This enables the verification of FCTLK formulas by using the fuzzy model checking algorithm of FCTL without additional computational overheads. Finally, we present correctness proofs and complexity analyses of the proposed algorithms. Additionally, we further illustrate the practical application of our approach through an example of a train control system

Evaluate Public-Private-Partnership’s advancement using double hierarchy hesitant fuzzy linguistic PROMETHEE with subjective and objective information from stakeholder perspective

Public-Private-Partnership (PPP) as an efficient mode to provide public services through the government and social capital’s cooperation has been in China for more than 30 years. In this paper, we propose an approach to evaluate PPP’s advancement in different areas based on the subjective and objective information fusion. At first, we establish an index system from the perspective of the stakeholder. Then, considering that double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) that has two hierarchies of linguistic term sets can describe the subjective linguistic information more accurately, it is applied in the paper to depict the subjective information. By applying the entropy of the DHHFLTS, a programming model is proposed to derive the attribute weight through combining subjective evaluation with objective data. In addition, we develop the double hierarchy hesitant fuzzy linguistic PROMETHEE combining the subjective and objective information (DHHFL-PROMETHEE-S&O) method. At last, we illustrate the index system and the method with the PPP’s advancement evaluation problem, and we can find the best choice based on the ranking result. Meanwhile, we also find that the objective information and the subjective information are complementary in the evaluation process. First published online 20 March 201

Diagnostic models of the pre-test probability of stable coronary artery disease: A systematic review

A comprehensive search of PubMed and Embase was performed in January 2015 to examine the available literature on validated diagnostic models of the pre-test probability of stable coronary artery disease and to describe the characteristics of the models. Studies that were designed to develop and validate diagnostic models of pre-test probability for stable coronary artery disease were included. Data regarding baseline patient characteristics, procedural characteristics, modeling methods, metrics of model performance, risk of bias, and clinical usefulness were extracted. Ten studies involving the development of 12 models and two studies focusing on external validation were identified. Seven models were validated internally, and seven models were validated externally. Discrimination varied between studies that were validated internally (C statistic 0.66-0.81) and externally (0.49-0.87). Only one study presented reclassification indices. The majority of better performing models included sex, age, symptoms, diabetes, smoking, and hyperlipidemia as variables. Only two diagnostic models evaluated the effects on clinical decision making processes or patient outcomes. Most diagnostic models of the pre-test probability of stable coronary artery disease have had modest success, and very few present data regarding the effects of these models on clinical decision making processes or patient outcomes

Constraining the interacting dark energy models from weak gravity conjecture and recent observations

We examine the effectiveness of the weak gravity conjecture in constraining the dark energy by comparing with observations. For general dark energy models with plausible phenomenological interactions between dark sectors, we find that although the weak gravity conjecture can constrain the dark energy, the constraint is looser than that from the observations.Comment: 14 pages, 12 figures, revtex4, v2: minor corrections, accepted for publication in PL