scholarly journals Spontaneous evolution of linguistic structure-an iterated learning model of the emergence of regularity and irregularity

2001 ◽  
Vol 5 (2) ◽  
pp. 102-110 ◽  
Author(s):  
S. Kirby
Keyword(s):  
Learning Model ◽  
Linguistic Structure ◽  
Iterated Learning ◽  
Spontaneous Evolution

scholarly journals Process Acceleration in the Iterated Learning Model with String Clipping

2015 ◽  
Vol 4 (2) ◽  
pp. 100-106 ◽  
Author(s):  
Ryuichi Matoba ◽  
Hiroki Sudo ◽  
Makoto Nakamura ◽  
Shingo Hagiwara ◽  
Satoshi Tojo
Keyword(s):  
Learning Model ◽  
Iterated Learning

Extension of iterated learning model based on real-world experiment

2020 ◽  
Author(s):  
R. Matoba ◽  
T. Yonezawa ◽  
S. Hagiwara ◽  
T. Cooper ◽  
M. Nakamura
Keyword(s):  
Real World ◽  
Learning Model ◽  
Model Based ◽  
Iterated Learning

Iterated Learning: A Framework for the Emergence of Language

2003 ◽  
Vol 9 (4) ◽  
pp. 371-386 ◽  
Author(s):  
Kenny Smith ◽  
Simon Kirby ◽  
Henry Brighton
Keyword(s):  
Language Learners ◽  
Cultural Evolution ◽  
Linguistic Structure ◽  
Learning Framework ◽  
Iterated Learning

Language is culturally transmitted. Iterated learning, the process by which the output of one individual's learning becomes the input to other individuals' learning, provides a framework for investigating the cultural evolution of linguistic structure. We present two models, based upon the iterated learning framework, which show that the poverty of the stimulus available to language learners leads to the emergence of linguistic structure. Compositionality is language's adaptation to stimulus poverty.

Modelling the “Aoristic Drift of the Present Perfect” as Inflation An Essay in Historical Pragmatics

2012 ◽  
Vol 4 (2) ◽  
pp. 261-292 ◽  
Author(s):  
Gerhard Schaden
Keyword(s):  
Language Change ◽  
Learning Model ◽  
Theoretical Issue ◽  
Past Tense ◽  
Causal Mechanism ◽  
Long Term Effects ◽  
Present Perfect ◽  
Linguistic System ◽  
Iterated Learning

In this article, the diachronic tendency of present perfect forms to become more and more past tense-like is analysed in terms of an inflationary process within an Iterated Learning Model. The paper proposes to improve on current accounts of the diachrony of present perfects (mostly set in the framework of grammaticalisation theory) by making explicit a selfreinforcing causal mechanism that drives the process, namely that speakers overestimate the current relevance contribution of their utterances. The main theoretical issue is to develop an explicit account of language change where modifications in a linguistic system are long-term effects of the use of language, or, put differently, of speaker-hearer interaction and the biases that act upon them.

The Nature of Words in Human Protolanguages: It's Not a Holophrastic-Atomic Meanings Dichotomy

2008 ◽  
Vol 14 (4) ◽  
pp. 445-465 ◽  
Author(s):  
Mike Dowman
Keyword(s):  
Learning Model ◽  
Human Language ◽  
Ongoing Debate ◽  
Iterated Learning

There is an ongoing debate as to whether the words in early presyntactic forms of human language had simple atomic meanings like modern words, or whether they were holophrastic. Simulations were conducted using an iterated learning model in which the agents were able to associate words with meanings, but in which they were not able to use syntactic rules to combine words into phrases or sentences. In some of these simulations words emerged that had neither holophrastic nor atomic meanings, demonstrating the possibility of protolanguages intermediate between these two extremes. Further simulations show how increases in cognitive or articulatory capacity would have produced changes in the type of words that was dominant in protolanguages. It is likely that at some point in time humans spoke a protolanguage in which most words had neither holophrastic nor atomic meanings.

scholarly journals The emergence of linguistic structure in an online iterated learning task

2017 ◽  
Vol 2 (2) ◽  
pp. 160-176 ◽  
Author(s):  
Clay Beckner ◽  
Janet B. Pierrehumbert ◽  
Jennifer Hay
Keyword(s):  
Learning Task ◽  
Linguistic Structure ◽  
Iterated Learning
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