DocumentCode
1472802
Title
Spontaneous evolution of linguistic structure-an iterated learning model of the emergence of regularity and irregularity
Author
Kirby, Simon
Author_Institution
Dept. of Linguistics, Edinburgh Univ., UK
Volume
5
Issue
2
fYear
2001
fDate
4/1/2001 12:00:00 AM
Firstpage
102
Lastpage
110
Abstract
A computationally implemented model of the transmission of linguistic behavior over time is presented. In this iterated learning model (ILM), there is no biological evolution, natural selection, nor any measurement of the success of the agents at communicating (except for results-gathering purposes). Nevertheless, counter to intuition, significant evolution of linguistic behavior is observed. From an initially unstructured communication system (a protolanguage), a fully compositional syntactic meaning-string mapping emerges. Furthermore, given a nonuniform frequency distribution over a meaning space and a production mechanism that prefers short strings, a realistic distribution of string lengths and patterns of stable irregularity emerges, suggesting that the ILM is a good model for the evolution of some of the fundamental features of human language
Keywords
digital simulation; grammars; iterative methods; learning (artificial intelligence); linguistics; multi-agent systems; ILM; fully compositional syntactic meaning-string mapping; irregularity emergence; iterated learning model; linguistic behavior transmission; linguistic structure evolution; meaning space; nonuniform frequency distribution; production mechanism; protolanguage; regularity emergence; spontaneous evolution; Biological system modeling; Biology computing; Computational modeling; Counting circuits; Evolution (biology); Humans; Induction generators; Natural languages; Signal generators; Signal mapping;
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/4235.918430
Filename
918430
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