Unlearning helps

Ganesh Baliga, John Case, Wolfgang Merkle, Frank Stephan

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

5 Scopus citations


Overregularization seen in child language learning, re verb tense constructs, involves abandoning correct behaviors for incorrect ones and later reverting to correct behaviors. Quite a number of other child development phenomena also follow this U-shaped form of learning, un- learning, and relearning. A decisive learner doesn’t do this and, in general, never abandons an hypothesis H for an inequivalent one where it later conjectures an hypothesis equivalent to H. The present paper shows that decisiveness is a real restriction on Gold’s model of iteratively (or in the limit) learning of grammars for languages from positive data. This suggests that natural U-shaped learning curves may not be a mere accident in the evolution of human learning, but may be necessary for learning. The result also solves an open problem. Second-time decisive learners conjecture each of their hypotheses for a language at most twice. By contrast, they are shown not to restrict Gold’s model of learning, and correspondingly, there is an apparent lack of re- ports in child development of the opposite, W-shaped learning curves.

Original languageEnglish (US)
Title of host publicationAutomata, Languages and Programming - 27th International Colloquium, ICALP 2000, Proceedings
EditorsUgo Montanari, Jose D. P. Rolim, Emo Welzl
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783540450221
StatePublished - 2000
Event27th International Colloquium on Automata, Languages and Programming, ICALP 2000 - Geneva, Switzerland
Duration: Jul 9 2000Jul 15 2000

Publication series

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


Other27th International Colloquium on Automata, Languages and Programming, ICALP 2000

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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