【摘要】：動態(tài)認知邏輯(DEL)是一種研究智能體認知狀態(tài)變化的一般邏輯方法,不僅可以用于推理多智能體系統(tǒng)(MAS)中的靜態(tài)認知性質(zhì),還可用于推理包含知識更新的MAS系統(tǒng)中的動態(tài)認知性質(zhì)。動態(tài)認知邏輯已在認知難題求解、認知規(guī)劃、安全通信協(xié)議、博弈論等多智能體系統(tǒng)研究領(lǐng)域得到越來越深入的應(yīng)用。本文面向一類多智能體認知難題,提出并實現(xiàn)一種擴展認知計算的μ演算邏輯及其符號化模型檢測算法,實驗結(jié)果表明我們方法的性能優(yōu)勢顯著。本文研究成果概括如下:首先設(shè)計一種建模描述語言,用于刻畫具有線性認知公告行為的認知難題;提出一種融合狀態(tài)遷移關(guān)系和智能體認知關(guān)系的認知公告形式模型;設(shè)計并實現(xiàn)了一個模型構(gòu)造算法,將含有認知公告行為的建模描述語言自動轉(zhuǎn)化為相應(yīng)的認知公告模型;通過在標準μ演算邏輯上擴展認知算子,提出一種新的認知μ演算邏輯,并在認知公告模型上提出了認知μ演算邏輯語義;設(shè)計并實現(xiàn)基于有序二元決策圖OBDD的認知μ演算符號化模型檢測算法;成功地對泥孩子、和與積這兩個MAS的經(jīng)典認知難題進行建模、求解、以及相關(guān)時態(tài)認知性質(zhì)的驗證。本文研究成果融合了μ演算、靜態(tài)認知、認知公告(一種動態(tài)認知邏輯)的建模與驗證方法。所提出的認知μ演算的時態(tài)表達能力不僅強于目前主流的時態(tài)認知模型檢測工具MCK、MCMAS和MCTK,而且也是動態(tài)認知模型檢測工具DEMO不具備的。上述兩個認知難題的實驗表明,本文方法的求解效率指數(shù)級優(yōu)于基于DEMO的方法。
[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)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP18

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