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Linked production rules: controlling inference with knowledge
conference contribution
posted on 2023-05-23, 09:53 authored by Compton, P, Kim, YS, Byeong KangByeong KangA key insight in artificial intelligence, which has been the foundation of expert systems and now business-rule systems, is that reasoning or inference can be separated from the domain knowledge being reasoned about. We suggest that the knowledge acquisition and maintenance problems that arise, might result from too great a separation of knowledge and inference. We propose Linked Production Rules, where each rule evaluated directs the next step of inference and the inference engine has no meta-heuristics or conflict resolution strategy. We suggest that this loses none of the power of conventional inference but may greatly improve knowledge acquisition and maintenance since various Ripple-Down Rule knowledge acquisition methods, which have had some success in facilitating knowledge maintenance can be described as specific instances of Linked Production Rules. Finally the Linked Production Rule approach suggests the possibility of a generalized Ripple-Down Rule method applicable to a wide range of problem types.
History
Publication title
Lecture Notes in Artificial Intelligence 8863: Proceedings of the 13th Pacific Rim Knowledge Acquisition Workshop (PKAW2014)Volume
8863Editors
YS Kim, BH Kang, D RichardsPagination
84-98ISSN
0302-9743Department/School
School of Information and Communication TechnologyPublisher
Springer International PublishingPlace of publication
SwitzerlandEvent title
2014 Pacific Rim Knowledge Acquisition Workshop (PKAW 2014)Event Venue
Gold Coast, AustraliaDate of Event (Start Date)
2014-12-01Date of Event (End Date)
2014-12-02Rights statement
Copyright 2014 Springer International Publishing SwitzerlandRepository Status
- Restricted