期刊名称：International Journal of Computer Science & Applications
印刷版ISSN：0972-9038
出版年度：2008
卷号：V
期号：I
页码：14-32
出版社：Technomathematics Research Foundation
摘要：Knowledge representation and reasoning aims at designing computer systems that reason about a
machineinterpretable
representation of the world, similar to human reasoning. Reasoning is a mechanism
which helps in retracting the previously inferred facts or changing the confidence factors when conditions
change while more complete information is received. This paper presents the design and implementation
of Gurukulam – nonmonotonic
reasoning based learning system which involves extended description
logics for knowledge representation. The knowledgebase is constructed by adapting the fundamental
classification of world knowledge concepts as per Nyaya Sastra, the famous Indian Philosophy. The
system simulates 5 student entities which inputs queries from the user interface and identifies the
knowledge units which are grouped into a suitable structure to be fed to the reasoning services engine.
Inferences are made from the submitted input and are later updated to their respective knowledge base.
Any knowledge base conflicts arising at this juncture is raised as doubts to the teaching entity for further
clarification. Upon user response, the system alters false beliefs which created conflicts during previous
inferences, thus demonstrating learning by nonmonotonic
reasoning.
