Generalisation towards combinatorial productivity in language acquisition by simple recurrent networks

Francis C.K. Wong, William Shi Yuan Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

Language exhibits combinatorial productivity as complex constructions are composed of simple elements In a linear or hierarchical fashion. Complexity arises as one cannot be exposed to all possible combinations during ontogeny and yet to master a language one need to be, and very often is, able to generalise to process and comprehend constructions that are of novel combinations. Accounting for such an ability is a current challenge being tackled In connectionist research. In this study, we will first demonstrate that connectionist networks do generalise towards combinatorial productivity followed by an investigation of how the networks could achieve that.
Original languageEnglish
Title of host publication2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007
Pages139-144
Number of pages6
DOIs
Publication statusPublished - 25 Sep 2007
Externally publishedYes
Event2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007 - Waltham, MA, United States
Duration: 30 Apr 20073 May 2007

Conference

Conference2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems, KIMAS 2007
Country/TerritoryUnited States
CityWaltham, MA
Period30/04/073/05/07

ASJC Scopus subject areas

  • Computer Science(all)

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