Model Checking Fuzzy Computation Tree Logic Based on Fuzzy Decision Processes with Cost

Abstract

In order to solve the problems in fuzzy computation tree logic model checking with cost operator, we propose a fuzzy decision process computation tree logic model checking method with cost. Firstly, we introduce a fuzzy decision process model with cost, which can not only describe the uncertain choice and transition possibility of systems, but also quantitatively describe the cost of the systems. Secondly, under the model of the fuzzy decision process with cost, we give the syntax and semantics of the fuzzy computation tree logic with cost operators. Thirdly, we study the problem of computation tree logic model checking for fuzzy decision process with cost, and give its matrix calculation method and algorithm. We use the example of medical expert systems to illustrate the method and model checking algorithm.

Quantitative reachability analysis of generalized possibilistic decision processes

“…However, in real life, there are some randomness, uncertainties and incon-sistencies that classical model checking is unable to express those information, such as a 90 percent probability of system crashing during operation [12]. To embed uncertain information into the model, quantitative model checking methods are proposed, including probabilistic model checking [4], possibilistic model checking [17], multi-valued model checking [10,11] and fuzzy model checking [2,12,18]. Quantitative reachability is to find the maximum probability [15] or the minimum probability [17].…”