The Computational Nature of Language Learning and Evolution

  title={The Computational Nature of Language Learning and Evolution},
  author={Partha Niyogi},
The nature of the interplay between language learning and the evolution of a language over generational time is subtle. We can observe the learning of language by children and marvel at the phenomenon of language acquisition; the evolution of a language, however, is not so directly experienced. Language learning by children is robust and reliable, but it cannot be perfect or languages would never change -- and English, for example, would not have evolved from the language of the Anglo-Saxon… 
Language Acquisition Meets Language Evolution
It is argued that understanding the acquisition of any cultural form, whether linguistic or otherwise, during development, requires considering the corresponding question of how that cultural form arose through processes of cultural evolution, which helps resolve the "logical" problem of language acquisition.
Learning Bias, Cultural Evolution of Language, and the Biological Evolution of the Language Faculty
A range of models and experimental studies are reviewed which show that weak biases in individual learners can have strong effects on the structure of sociallylearned systems such as language, suggesting that strong universal tendencies in language structure do not require us to postulate strong underlying biases or constraints on language learning.
Models of Language Evolution
The levels of linguistic structure, and why the emergence of structure in language is a central question for evolutionary linguistics are discussed, and how learning biases at the individual level lead to the presence of typological universals are discussed.
Grammar Structure and the Dynamics of Language Evolution
This study finds that coherence emerges with lower learning fidelity than predicted by earlier work with an unstructured language space, and includes grammars inspired by the principles and parameters paradigm.
Emergence of Scale-Free Syntax Networks
A previously unreported, sharp transition is shown to occur around two years of age from a (pre-syntactic) tree-like structure to a scale-free, small world syntax network, which introduces a new ingredient to understand the possible biological endowment of human beings which results in the emergence of complex language.
Quantifying the evolutionary dynamics of language
This study provides a quantitative analysis of the regularization process by which ancestral forms gradually yield to an emerging linguistic rule, and studies how the rate of regularization depends on the frequency of word usage.
Language Change across Generations for Robots using Cognitive Maps
It is demonstrated that the rate of language change depends on learning periods and concept formation, and that the language transmission bottleneck reduces the retention of words that are part of large lexicons more than words that is part of small lexicons.
Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift
It is shown that the transmission of frequency distributions over variants of linguistic forms by Bayesian learners is equivalent to the Wright–Fisher model of genetic drift, which allows a ‘neutral’ model to be defined that indicates how languages can change in the absence of selection at the level of linguistic variants.


Evolution of universal grammar.
This work presents a mathematical framework for the evolutionary dynamics of grammar learning and calculates the condition under which natural selection favors the emergence of rule-based, generative grammars that underlie complex language.
Language Identification in the Limit
  • E. M. Gold
  • Linguistics, Computer Science
    Inf. Control.
  • 1967
Cultural transmission and evolution: a quantitative approach.
A mathematical theory of the non-genetic transmission of cultural traits is developed that provides a framework for future investigations in quantitative social and anthropological science and concludes that cultural transmission is an essential factor in the study of cultural change.
He works on computational modeling of concept acquisition under the influence of language; he then uses insights gained from this to construct cognitive systems for AI and robotic applications
    Language identification
    • 1967