Title :
A framework for comparative analysis of belief revision models in rule-based systems
Author :
Schocken, Shimon
Author_Institution :
Leonard N. Stern Sch. of Bus., New York Univ., NY, USA
Abstract :
Belief revision in standard rule-based systems is NP-hard, and it is necessary to resort to quasiprobabilistic belief languages which are quite problematic on normative grounds. The author presents a framework designed to study the Bayesian interpretation and cognitive appeal of these languages. He uses this framework to review some well-known and some recent findings, and comments on the merit of alternative approaches to belief revision in rule-based systems
Keywords :
Bayes methods; computational complexity; formal languages; knowledge based systems; probability; Bayesian interpretation; NP hard problem; belief revision models; cognitive appeal; comparative analysis; normative grounds; quasiprobabilistic belief languages; rule-based systems; Artificial intelligence; Bayesian methods; Engines; Expert systems; Humans; Inference algorithms; Knowledge based systems; Testing; Uncertainty;
Conference_Titel :
System Sciences, 1989. Vol.III: Decision Support and Knowledge Based Systems Track, Proceedings of the Twenty-Second Annual Hawaii International Conference on
Conference_Location :
Kailua-Kona, HI
Print_ISBN :
0-8186-1913-9
DOI :
10.1109/HICSS.1989.49173
