A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2007; you can also visit the original URL.
The file type is application/pdf
.
APPRENTICESHIP LEARNING IN IMPERFECT DOMAIN THEORIES
[chapter]
1990
Machine Learning
This chapter presents DISCIPLE, a multi-strategy integrated learning system illustrating a theory and a methodology for learning expert knowledge in the context of an imperfect domain theory. DISCIPLE integrates a learning system and an empty expert system, both using the same knowledge base. It is initially provided with an imperfect (nonhomogeneous) domain theory and learns problem solving rules from the problem solving steps received from its expert user, during interactive problem solving
doi:10.1016/b978-0-08-051055-2.50028-6
fatcat:f25bne7gkfaplifraikje4mwae