Co-learning and the development of communication

Viktor Gyenes, András Lorincz

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

Abstract

We investigate the properties of coupled co-learning systems during the emergence of communication. Co-learning systems are more complex than individual learning systems because of being dependent on the learning process of each other, thus risking divergence. We developed a neural network approach and implemented a concept that we call reconstruction principle, which we found adequate for overcoming the instability problem. Experimental simulations were performed to test the emergence of both compositional and holistic communication. The results show that compositional communication is favorable when learning performance is considered, however it is more error-prone to differences in the conceptual representations of the individual systems. We show that our architecture enables the adjustment of the differences in the individual representations in case of compositional communication.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 2007 - 17th International Conference, Proceedings
PublisherSpringer Verlag
Pages827-837
Number of pages11
EditionPART 1
ISBN (Print)9783540746898
DOIs
Publication statusPublished - 2007
Event17th International Conference on Artificial Neural Networks, ICANN 2007 - Porto, Portugal
Duration: Sep 9 2007Sep 13 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4668 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other17th International Conference on Artificial Neural Networks, ICANN 2007
CountryPortugal
CityPorto
Period9/9/079/13/07

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Gyenes, V., & Lorincz, A. (2007). Co-learning and the development of communication. In Artificial Neural Networks - ICANN 2007 - 17th International Conference, Proceedings (PART 1 ed., pp. 827-837). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4668 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-74690-4_84