Can iterated learning explain the emergence of graphical symbols?

2012 ◽  
pp. 33-50
Author(s):  
Simon Garrod ◽  
Nicolas Fay ◽  
Shane Rogers ◽  
Bradley Walker ◽  
Nik Swoboda
Keyword(s):  
Iterated Learning

scholarly journals Compositional Hierarchical Structure Evolves through Cultural Transmission: An Experimental Study

2019 ◽  
Vol 4 (2) ◽  
pp. 83-107 ◽  
Author(s):  
Carmen Saldana ◽  
Simon Kirby ◽  
Robert Truswell ◽  
Kenny Smith
Keyword(s):  
Language Learning ◽  
Language Learners ◽  
Hierarchical Structure ◽  
Cultural Transmission ◽  
Artificial Language ◽  
Compositional Structure ◽  
Evolutionary Linguistics ◽  
Artificial Language Learning ◽  
Learning Techniques ◽  
Iterated Learning

AbstractCompositional hierarchical structure is a prerequisite for productive languages; it allows language learners to express and understand an infinity of meanings from finite sources (i.e., a lexicon and a grammar). Understanding how such structure evolved is central to evolutionary linguistics. Previous work combining artificial language learning and iterated learning techniques has shown how basic compositional structure can evolve from the trade-off between learnability and expressivity pressures at play in language transmission. In the present study we show, across two experiments, how the same mechanisms involved in the evolution of basic compositionality can also lead to the evolution of compositional hierarchical structure. We thus provide experimental evidence showing that cultural transmission allows advantages of compositional hierarchical structure in language learning and use to permeate language as a system of behaviour.

scholarly journals Sequence Memory Constraints Give Rise to Language-Like Structure through Iterated Learning

PLoS ONE ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. e0168532 ◽  
Author(s):  
Hannah Cornish ◽  
Rick Dale ◽  
Simon Kirby ◽  
Morten H. Christiansen
Keyword(s):  
Iterated Learning ◽  
Sequence Memory ◽  
Memory Constraints

Using Category Structures to Test Iterated Learning as a Method for Identifying Inductive Biases

2008 ◽  
Vol 32 (1) ◽  
pp. 68-107 ◽  
Author(s):  
Thomas L. Griffiths ◽  
Brian R. Christian ◽  
Michael L. Kalish
Keyword(s):  
Iterated Learning

scholarly journals The emergence of duality of patterning through iterated learning: Precursors to phonology in a visual lexicon

2012 ◽  
Vol 4 (4) ◽  
pp. 381-418 ◽  
Author(s):  
Alex Del Giudice
Keyword(s):  
Design Feature ◽  
Combinatorial Structure ◽  
Human Language ◽  
Lexical Structure ◽  
Small Stock ◽  
Iterated Learning ◽  
Human Participants ◽  
Duality Of Patterning ◽  
Future Work ◽  
Infinite Set

AbstractDuality of Patterning, one of Hockett's (1960) proposed design features unique to human language, refers in part to the arrangements of a relatively small stock of distinguishable meaningless sounds which are combined to create a potentially infinite set of morphemes. Literature regarding the emergence of this design feature is less abundant than that exploring other levels of structure as focus is more often given to the emergence of syntax. In an effort to explore where combinatorial structure of meaningless elements arises the results of two pilot experiments are presented within which we observe human participants modifying a small lexicon of visual symbols through a process of iterated learning. As this lexicon evolves there is evidence that it becomes simpler and more learnable, more easily transmitted. I argue that these features are a consequence of spontaneous emergence of combinatorial, sub-lexical structure in the lexicon, that the pattern of emergence is more complex than the most widely espoused explanation suggests, and I propose ways in which future work can build on what we learn from these pilot experiments to confirm this hypothesis.

scholarly journals The emergence of word-internal repetition through iterated learning: Explaining the mismatch between learning biases and language design

2020 ◽  
Author(s):  
Mitsuhiko Ota ◽  
Aitor San José ◽  
Kenny Smith
Keyword(s):  
Cultural Transmission ◽  
Relative Strength ◽  
Language Design ◽  
Test Case ◽  
Artificial Language ◽  
Natural Languages ◽  
Learning Biases ◽  
Linguistic System ◽  
Iterated Learning ◽  
Cultural Evolutionary

The idea that natural language is shaped by biases in learning plays a key role in our understanding of how human language is structured, but its corollary that there should be a correspondence between typological generalisations and ease of acquisition is not always supported. For example, natural languages tend to avoid close repetitions of consonants within a word, but developmental evidence suggests that, if anything, words containing sound repetitions are more, not less, likely to be acquired than those without. In this study, we use word-internal repetition as a test case to provide a cultural evolutionary explanation of when and how learning biases impact on language design. Two artificial language experiments showed that adult speakers possess a bias for both consonant and vowel repetitions when learning novel words, but the effects of this bias were observable in language transmission only when there was a relatively high learning pressure on the lexicon. Based on these results, we argue that whether the design of a language reflects biases in learning depends on the relative strength of pressures from learnability and communication efficiency exerted on the linguistic system during cultural transmission.

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