Title :
Genetics-based self-adjusting expert systems
Author :
Pakath, Ramakrishnan
Author_Institution :
Dept. of Decision Sci. & Inf. Syst., Kentucky Univ., Lexington, KY, USA
Abstract :
The conventional rule-based expert system (ES) paradigm has been criticized because of its inability to display characteristics of true intelligence and its relatively static knowledge storehouse and dependence on rote-learned rule fragments as a basis for reasoning. An approach to constructing self-adjusting ESs is described. Self-adjusting ESs are characterized by their dynamic knowledge bases that improve with experience and their ability to pursue unfocused reasoning. An implementation of the paradigm is examined and its traits in light of the criticisms leveled against its predecessor are evaluated
Keywords :
expert systems; inference mechanisms; self-adjusting systems; dynamic knowledge bases; genetics-based ES; self-adjusting ESs; self-adjusting expert systems; unfocused reasoning; Business; Displays; Educational institutions; Electronic switching systems; Expert systems; Information systems; Learning systems; Machine learning; Medical expert systems; Scheduling;
Conference_Titel :
System Sciences, 1993, Proceeding of the Twenty-Sixth Hawaii International Conference on
Conference_Location :
Wailea, HI
Print_ISBN :
0-8186-3230-5
DOI :
10.1109/HICSS.1993.284330
