Knowledge representation and reasoning method based on relation database 一種基于關系數(shù)據(jù)庫的知識表示和推理方法
During the study on the realization of computer - aided conceptual design system of mechanism design , the thesis utilized some knowledge and technology in the artificial intelligence field such as knowledge representation and reasoning 在對計算機輔助機構概念設計系統(tǒng)的實現(xiàn)的研究中,論文利用了人工智能領域中的知識表示和推理等知識與技術。
16 rendell d a , cui z , cohn a g . a spatial logic based on regions and connection . international conference on knowledge representation and reasoning , 1992 , pp . 165 - 176 . 17 fiadeiro jos e l . categories for software engineering 進一步把帶類型范疇的概念推廣為類范疇,可以描述不完全和有缺陷的知識,以及不完全知識和有缺陷知識消除缺陷和完備化的過程。
This paper describes the details about knowledge representation and reasoning based on uncertainty in ai , and the outline of belief network . after introducing the causality diagram model and summarizing conventional reasoning algorithm , a new reasoning approach of causality diagram has been presented , which is aimed at the defects in conventional reasoning algorithm , which are the large amount of boolean computation and its complexity 論文詳細地介紹了人工智能中不確定性知識表達及其推理的有關內容,并簡要介紹了信度網知識表達方式;在介紹因果圖知識表達模型、總結單值因果圖的常規(guī)推理算法后,針對單值因果圖常規(guī)推理算法中存在邏輯運算量大、計算復雜的困難,根據(jù)早期不交化的思想,提出了一種單值因果圖推理的新方法。
This dissertation discusses and studies to surround the knowledge representation , learning , reasoning , and the main contents include : at the first chapter , some familiar uncertain knowledge representation and reasoning and the difficulties of them : evidential theory , certainty factor , fuzzy logic and fuzzy reasoning , subjective bayesian method , belief network are introduced . we present the basic knowledge , primary reasoning algorithm , complexity of reasoning algorithm , the way of dealing with some problem of causality diagram relative and the research direction in causality diagram theory particular at the second chapter 論文圍繞著因果圖的知識表達、學習、推理進行了討論和研究,主要內容包括:在扼要介紹了一些比較常見的不確定性知識的表示和推理方法:證據(jù)理論、確定性因子、模糊邏輯與模糊推理、主觀bayes方法、信度網的基本知識之后,比較詳細地闡述了因果圖的知識表達,主要的推理算法、計算復雜度以及對一些問題的處理方式方法。
百科解釋
Knowledge representation (KR) is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge. The KR can be made to be independent of the underlying knowledge model or knowledge base system (KBS) such as a semantic network.