Connectionist expert system with adaptive learning capability

• Main Authors: LOW, B. T., LUI, Hochung, TAN, Ah-hwee, TEH, Hoonheng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 1991
• Subjects: Hybrid intelligent systems; Adaptive systems; Pattern matching; Diagnostic expert systems; Neural networks; Logic programming; Expert systems; Knowledge acquisition; Medical expert systems; Frequency; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5200; https://ink.library.smu.edu.sg/context/sis_research/article/6203/viewcontent/k0200.pdf
• Institution: Singapore Management University

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.