Communications of the ACM
Learning one subprocedure per lesson
Artificial Intelligence
Incremental version-space merging: a general framework for concept learning
Incremental version-space merging: a general framework for concept learning
Learning from plausible explanations
Proceedings of the sixth international workshop on Machine learning
A Study of Explanation-Based Methods for Inductive Learning
Machine Learning
Explanation-Based Generalization: A Unifying View
Machine Learning
Induction in an abstraction space: a form of constructive induction
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
The complexity of theory revision
Artificial Intelligence
| Hi-index | 0.00 |
One of the "grand challenges for machine learning" is the problem of learning from textbooks. This paper addresses the problem of learning from texts including omissions and inconsistencies that are clarified by illustrative examples. To avoid problems in natural language understanding, we consider a simplification of this problem in which the text has been manually translated into a logical theory. This learning problem is solvable by a technique that we call analogical abductive explanation based learning (ANA-EBL). Formal evidence and experimental results in the domain of contract bridge show that the learning technique is both efficient and effective.