A review of learning
- 1 September 1991
- journal article
- review article
- Published by Cambridge University Press (CUP) in The Knowledge Engineering Review
- Vol. 6 (3), 195-222
- https://doi.org/10.1017/s0269888900005804
Abstract
Learning is one of the important research fields in artificial intelligence. This paper begins with an outline of the definitions of learning and intelligence, followed by a discussion of the aims of machine learning as an emerging science, and an historical outline of machine learning. The paper then examines the elements and various classifications of learning, and then introduces a new classification of learning based on the levels of representation and learning as knowledge-, symboland device-level learning. Similarity- and explanation-based generalization and conceptual clustering are described as knowledge level learning methods. Learning in classifiers, genetic algorithms and classifier systems are described as symbol level learning, and neural networks are described as device level systems. In accordance with this classification, methods of learning are described in terms of inputs, learning algorithms or devices, and outputs. Then there follows a discussion on the relationships between knowledge representation and learning, and a discussion on the limits of learning in knowledge systems. The paper concludes with a summary of the results drawn from this review.Keywords
This publication has 32 references indexed in Scilit:
- Evolution of a knowledge‐based system for determining structural components of proteinsExpert Systems, 1989
- Computational Philosophy of SciencePublished by MIT Press ,1988
- The role of frame-based representation in reasoningCommunications of the ACM, 1985
- Qualitative process theoryArtificial Intelligence, 1984
- Logical levels of problem solvingThe Journal of Logic Programming, 1984
- Logic Programming in the Fifth GenerationThe Knowledge Engineering Review, 1984
- Eurisko: A program that learns new heuristics and domain concepts: The nature of Heuristics III: Program design and resultsArtificial Intelligence, 1983
- Search and Reasoning in problem solvingArtificial Intelligence, 1983
- Data‐Driven Discovery of Physical LawsCognitive Science, 1981
- The perceptron: A probabilistic model for information storage and organization in the brain.Psychological Review, 1958