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Uncertainties and the flexible logics

Authors :
Hua Wang
Li-Rong Ai
Hua-Can He
Source :
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).
Publication Year :
2004
Publisher :
IEEE, 2004.

Abstract

How to deal with various uncertainties and evolution has been a critical problem for further development of AI. The well-developed mathematical logic is too rigid and it can only solve certain problems. It is a new challenge for logics to make mathematical logic more flexible and can contain various uncertainties and evolution. This has been studied by the academic community for several years and has made some breakthroughs at some isolated points, but a systematic theory has not come into being. The flexible propositional logics is put forward on the basis of our study of the general logical rules in real world, which can include quite a few kinds of known uncertainty reasoning models, such as probability, belief, likelihood, certainty, possibility and fuzzy reasoning, and so on. Moreover, it lays the theoretical basis for the study of more complex uncertainty problems and evolution problems.

Details

Database :
OpenAIRE
Journal :
Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693)
Accession number :
edsair.doi...........d0d672f5e84eb2344c1a2dc72e28b743
Full Text :
https://doi.org/10.1109/icmlc.2003.1259949