基于μ演算的認(rèn)知難題符號(hào)化模型檢測(cè)
[Abstract]:Dynamic cognitive logic (DEL) is a general logical method to study the change of agent cognitive state, which can not only be used to reason the static cognitive properties of multi-agent system (MAS). It can also be used to infer dynamic cognitive properties in MAS systems containing knowledge updates. Dynamic cognitive logic has been more and more deeply applied in the research fields of cognitive problem solving, cognitive planning, secure communication protocol, game theory and so on. In this paper, aiming at a class of multi-agent cognitive problems, a 渭 arithmetic logic and its symbolic model detection algorithm for extended cognitive computing are proposed and implemented. The experimental results show that our method has significant performance advantages. The research results of this paper are summarized as follows: firstly, a modeling description language is designed to describe the cognitive problems with linear cognitive announcement behavior, and a cognitive announcement formal model combining state transition relationship and agent cognitive relationship is proposed. A model construction algorithm is designed and implemented, which automatically converts the modeling description language with cognitive announcement behavior into the corresponding cognitive announcement model. By extending the cognitive operator in the standard 渭 logic, a new cognitive 渭 logic is proposed, and the cognitive 渭 logic semantics is proposed on the cognitive announcement model. The symbolic model detection algorithm of cognitive 渭 calculation based on ordered binary decision graph OBDD is designed and implemented, and the classical cognitive problems of mud child, sum and product are successfully modeled, solved and verified by the relevant temporal cognitive properties. The research results of this paper combine the modeling and verification methods of 渭 calculus, static cognition and cognitive announcement (a dynamic cognitive logic). The temporal expression ability of the proposed cognitive 渭 calculus is not only stronger than the current mainstream temporal cognitive model detection tools MCK,MCMAS and MCTK, but also not available to the dynamic cognitive model detection tool DEMO. The experiments of the above two cognitive problems show that the proposed method is superior to the DEMO-based method in solving the efficiency index.
【學(xué)位授予單位】:華僑大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類(lèi)號(hào)】:TP18
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