A perceptual criterion for visually controlling learning

Masaki Suwa, Hiroshi Motoda

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Acquiring search control knowledge of high utility is essential to reasoners in speeding up their problem-solving performance. In the domain of geometry problem-solving, the role of “perceptual chunks”, an assembly of diagram elements many problems share in common, in effectively guiding problem-solving search has been extensively studied, but the issue of learning these chunks from experiences has not been addressed so far. Although the explanation-based learning technique is a typical learner for search control knowledge, the goal-orientedness of its chunking criterion leads to produce such search control knowledge that can only be used for directly accomplishing a target-concept, which is totally different from what perceptual-chunks are for. This paper addresses the issues of acquiring domain-specific perceptual-chunks and demonstrating the utility of acquired chunks. The proposed technique is that the learner acquires, for each control decision node in the problem solving traces, a chunk which is an assembly of diagram elements that can be visually recognizable and grouped together with the control decision node. Recognition rules implement this chunking criterion in the learning system PCLEARN. We show the feasibility of the proposed technique by investigating the applicability and cost-effective utility of the learned perceptual chunks in the geometry domain.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 4th International Workshop, ALT 1993, Proceedings
EditorsKlaus P. Jantke, Shigenobu Kobayashi, Etsuji Tomita, Takashi Yokomori
PublisherSpringer Verlag
Number of pages14
ISBN (Print)9783540573708
Publication statusPublished - 1993
Externally publishedYes
Event4th Workshop on Algorithmic Learning Theory, ALT 1993 - Tokyo, Japan
Duration: 1993 Nov 81993 Nov 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume744 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other4th Workshop on Algorithmic Learning Theory, ALT 1993

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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