Browsing by Author "Krawchuk, Brent J."
Now showing 1 - 3 of 3
Results Per Page
- ItemOpen AccessEXPLANATION-BASED LEARNING: ITS ROLE IN PROBLEM SOLVING(1988-06-01) Krawchuk, Brent J.; Witten, Ian H."Explanation-based" learning is a semantically-driven, knowledge-intensive paradigm for machine learning which contrasts sharply with syntactic or "similarity-based" approaches. This paper redevelops the foundations of EBL from the perspective of problem-solving. Viewed in this light, the technique is revealed as a simple modification to an inference engine which gives it the ability to generalize the conditions under which the solution to a particular problem holds. We show how to embed generalization invisibly within the problem solver, so that it is accomplished as inference proceeds rather than as a separate step. The approach is also extended to the more complex domain of planning, which involves maintaining and operating on a global world state, to illustrate that it is by no means restricted to toy problem-solvers. We argue against the current trend to isolate learning from other activity and study it separately, preferring instead to integrate it into the very heart of problem solving.
- ItemOpen AccessON ASKING THE RIGHT QUESTIONS(1988-01-01) Witten, Ian H.; Krawchuk, Brent J.Concept learning systems have a great deal to gain by showing more initiative; in particular, by actively posing test examples rather than passively waiting for more examples to appear. This paper briefly reviews different approaches to selecting examples, and goes on to explore the ramifications of one in detail. Current implementations are overly simplistic because they assume a hierarchically-structured network of concepts. It is shown how they break down in more general partially-ordered domains, and a new method which copes with this situation is described and illustrated. Finally, the techniques are related to the version-space approach to provide them with a well-understood theoretical underpinning.