Conferences in Research and Practice in Information Technology
  

Online Version - Last Updated - 20 Jan 2012

 

 
Home
 

 
Procedures and Resources for Authors

 
Information and Resources for Volume Editors
 

 
Orders and Subscriptions
 

 
Published Articles

 
Upcoming Volumes
 

 
Contact Us
 

 
Useful External Links
 

 
CRPIT Site Search
 
    

An algorithm for the induction of defeasible logic theories from databases

Johnston, B. and Governatori, G.

    Defeasible logic is a non-monotonic logic with applications in rule-based domains such as law. To ease the development and improve the accuracy of expert systems based on defeasible logic, it is desirable to automatically induce a theory of the logic from a training set of precedent data. Empirical evidence suggests that minimal theories that describe the training set tend to be more faithful representations of reality. We show via transformation from the hitting set problem that this global minimization problem is intractable, belonging to the class of NP optimisation problems. Given the inherent difficulty of finding the optimal solution, we instead use heuristics and demonstrate that a best-first, greedy, branch and bound algorithm can be used to find good theories in short time. This approach displays significant improvements in both accuracy and theory size as compared to recent work in the area that post-processed the output of an Apriori association rule-mining algorithm, with comparable execution times.
Cite as: Johnston, B. and Governatori, G. (2003). An algorithm for the induction of defeasible logic theories from databases. In Proc. Fourteenth Australasian Database Conference (ADC2003), Adelaide, Australia. CRPIT, 17. Schewe, K.-D. and Zhou, X., Eds. ACS. 75-83.
pdf (from crpit.com) pdf (local if available) BibTeX EndNote GS
 

 

ACS Logo© Copyright Australian Computer Society Inc. 2001-2014.
Comments should be sent to the webmaster at crpit@scem.uws.edu.au.
This page last updated 16 Nov 2007