不完全与不协调知识表示及推理

This project studies on the incomplete and inconsistent knowledge representation and reasoning, which aims to provide logical foundations and implementation algorithms for reasoning with incomplete and inconsistent knowledge. Nonmonotonic paraconsistent logics are proposed and developed. Some fundamental problems of nonmonotonic logics, paraconsistent logics, description logics and argument systems are solved. A technical approach to the treatment of incomplete and inconsistent knowledge is provided. The theories and standards of the semantic Web for incomplete and inconsistent ontology are established. The incomplete and inconsistent knowledge representation and reasoning has important scientific significance and wide application in computer science and artificial intelligence, and serves as theoretic basis and key technology for non-canonical knowledge management, commonsense reasoning, knowledge-based systems, knowledge and ontology bases, big data mining, semantic Web and complex software systems in dynamic environment.

本项目研究不完全与不协调知识表示与推理，旨在提供不完全与不协调知识下推理的逻辑基础和实现算法，提出并发展非单调超协调逻辑，解决非单调逻辑、超协调逻辑、描述逻辑和辩论系统各自存在的一些基础问题，提供一种不完全与不协调知识处理的技术途径，并应用来建立不完全与不协调语义Web本体的理论基础和标准。不完全与不协调知识表示与推理在计算机科学与人工智能中具有重要的科学意义和广泛的应用，对于处理非规范知识、常识推理、基于知识的系统、知识库和本体库、大数据挖据、语义Web和动态环境下复杂软件系统都是重要的理论基础和关键技术。

本项目研究不完全与不协调知识表示与推理，提出并发展了非单调超协调逻辑，解决了非单调超协调逻辑存在的一些基础问题，提供了一种不完全与不协调知识处理的技术途径，并应用来建立不完全与不协调语义Web本体的理论基础。不完全与不协调知识表示与推理在人工智能中具有重要的科学意义和广泛的应用前景。