Abstract
This paper deals with the extraction of default rules from a database of examples. The proposed approach is based on a special kind of probability distributions, called big-stepped probabilities. It has been shown that these distributions provide a semantics for the System P developed by Kraus, Lehmann et Magidor for representing non-monotonic consequence relations. Thus the rules which are learnt are genuine default rules, which could be used (under some conditions) in a nonmonotonic reasoning system, which can be encoded in possibilistic logic.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
