Title :
Application of hybrid logic in inference of Knowware System
Author :
Lo, Sio-Long ; Ding, Li-ya ; Chen, Yuan
Author_Institution :
Fac. of Inf. Technol., Macau Univ. of Sci. & Technol., Macau, China
Abstract :
Handling of uncertainty has been an important topic discussed in the community of intelligent techniques and soft computing. It is necessary to represent human knowledge and modeling its uncertainty when developing an intelligent system. There are various types of uncertainty in the real world, and randomness and fuzziness are of two basic kinds. How to handle these two kinds of uncertainties appearing simultaneously in a system is a main task of intelligent system development. The Knowware System (KWS) has been developed as an intelligent tool for modeling and development of knowledge-based system (KBS). It is to support application developers in constructing customized hybrid intelligent system without the necessity of being familiar with relevant AI techniques. Modeling and processing uncertainty of different types has its significance for further enhancement of KWS mechanism to better support real applications. In this paper, we will present the modeling of KBS with possible uncertainty and the propose handling hybrid uncertainty in inference of KWS, which includes randomness and fuzziness, based on the hybrid logic and chance theory.
Keywords :
formal logic; inference mechanisms; knowledge based systems; uncertainty handling; hybrid logic; intelligent system development; knowledge-based system; knowware system; system inference; uncertainty handling; Cognition; Cybernetics; Knowledge based systems; Machine learning; Rain; Uncertainty; Chance theory; Credibility theory; Fuzziness; Hybrid logic; Knowware system; Randomness; Uncertainty;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580950