Abstraction in problem solving and learning

Authors:
Amy Unruh;Paul S. Rosenbloom
Affiliations:
Computer Science Dept., Stanford University, Palo Alto, CA;Information Sciences Institute, University of Southern California, Marina del Rey, CA
Venue:
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Year:
1989

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Abstract

Abstraction has proven to be a powerful tool for controlling the combinatorics of a problemsolving search. It is also of critical importance for learning systems. In this article we present, and evaluate experimentally, a general abstraction method -- impasse-driven abstraction - which is able to provide necessary assistance to both problem solving and learning. It reduces the amount of time required to solve problems, and the time required to learn new rules. In addition, it results in the acquisition of rules that are more general than would have otherwise been learned.