The advantages of abstract control knowledge in expert system design

作者: William J. Clancey

DOI:

关键词:

摘要: A poorly designed knowledge base can be as cryptic an arbitrary program and just difficult to maintain. Representing control abstractly, separately from domain facts relations, makes the design more transparent explainable. body of abstract provides a generic framework for constructing bases related problems in other domains also useful starting point studying nature strategies.

参考文章(16)
Mark Jeffrey Stefik, Planning with constraints Stanford University. ,(1980)
Janice S. Aikins, Representation of control knowledge in expert systems national conference on artificial intelligence. pp. 121- 123 ,(1980)
Diane Warner Hasling, Abstract explanations of strategy in a diagnostic consultation system national conference on artificial intelligence. pp. 157- 161 ,(1983)
Bob London, William J. Clancey, Plan recognition strategies in student modeling: prediction and description national conference on artificial intelligence. pp. 335- 338 ,(1982)
Susan P. Ennis, Expert systems a user's perspective of some current tools national conference on artificial intelligence. pp. 319- 321 ,(1982)
William R. Swartout, A DIGITALIS THERAPY ADVISOR WITH EXPLANATIONS international joint conference on artificial intelligence. pp. 819- 825 ,(1977)
William R. Swartout, Explaining and justifying expert consulting programs international joint conference on artificial intelligence. pp. 815- 823 ,(1981) , 10.1007/978-1-4612-5108-8_15
Reed Letsinger, William J. Clancey, NEOMYCIN: reconfiguring a rule-based expert system for application to teaching international joint conference on artificial intelligence. pp. 829- 836 ,(1981)
J. M. Nicolas, H. Gallaire, Data Base: Theory vs. Interpretation Logic and Data Bases. pp. 33- 54 ,(1978) , 10.1007/978-1-4684-3384-5_2