The simulation of verbal learning behavior
Computers & thought
Learning Structural Descriptions From Examples
Learning Structural Descriptions From Examples
Version spaces: an approach to concept learning.
Version spaces: an approach to concept learning.
Decomposition, merging, and refinement approach to boost inductive logic programming algorithms
AIMSA'12 Proceedings of the 15th international conference on Artificial Intelligence: methodology, systems, and applications
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A system learning concepts from training samples consisting of structured objects is described. It is based on descriptions invariant under isomorphism. In order to get a unified mathematical formalism recent graph theoretic results are used- The structures are transformed into feature vectors and after that a concept learning algorithm developing decision trees is applied which is an extension of algorithms found in psychological experiments. It corresponds to a general-to-specific depth-first search with reexamination of past events. The generalization ability is demonstrated by means of the blocks world example and it is shown that the algorithm can successfully handle practical problems with samples of about one hundred of relatively complicated structures in a reasonable time. Additionally, the problem of representation and learning context dependent concepts is discussed in the paper.