Title :
Connectionist expert system with adaptive learning capability
Author :
Low, B.T. ; Lui, H.C. ; Tan, A.H. ; Teh, H.H.
Author_Institution :
Inst. of Syst. Sci., Nat. Univ. of Singapore, Singapore
fDate :
6/1/1991 12:00:00 AM
Abstract :
A neural network expert system called adaptive connectionist expert system (ACES) which will learn adaptively from past experience is described. ACES is based on the neural logic network, which is capable of doing both pattern processing and logical inferencing. The authors discuss two strategies, pattern matching ACES and rule inferencing ACES. The pattern matching ACES makes use of past examples to construct its neural logic network and fine-tunes itself adaptively during its use by further examples supplied. The rule inferencing ACES conceptualizes new rules based on the frequencies of use on the rule-based neural logic network. A new rule could be considered as a pattern matching example and be incorporated into pattern matching ACES
Keywords :
adaptive systems; expert systems; inference mechanisms; neural nets; pattern recognition; adaptive connectionist expert system; adaptive learning capability; logical inferencing; neural logic network; neural network expert system; past examples; past experience; pattern matching ACES; pattern processing; rule inferencing ACES; Adaptive systems; Diagnostic expert systems; Expert systems; Frequency; Hybrid intelligent systems; Knowledge acquisition; Logic programming; Medical expert systems; Neural networks; Pattern matching;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on