Conceptual and Methodological Problems with Comparative Work on Artificial Language Learning

Several theoretical proposals for the evolution of language have sparked a renewed search for comparative data on human and non-human animal computational capacities. However, conceptual confusions still hinder the field, leading to experimental evidence that fails to test for comparable human competences. Here we focus on two conceptual and methodological challenges that affect the field generally: 1) properly characterizing the computational features of the faculty of language in the narrow sense; 2) defining and probing for human language-like computations via artificial language learning experiments in non-human animals. Our intent is to be critical in the service of clarity, in what we agree is an important approach to understanding how language evolved.

[1]  Noam Chomsky,et al.  The faculty of language: what is it, who has it, and how did it evolve? , 2002, Science.

[2]  C. Gallistel.  The organization of learning , 1990 .

[3]  S. Barry Cooper,et al.  Solvable and Unsolvable Problems , 2013 .

[4]  A. Rey,et al.  Centre-embedded structures are a by-product of associative learning and working memory constraints: Evidence from baboons (Papio Papio) , 2012, Cognition.

[5]  Denise Brandão de Oliveira e Britto,et al.  The faculty of language , 2007 .

[6]  Esther Mondragón,et al.  Rule Learning by Rats , 2008, Science.

[7]  James Rogers,et al.  12. The use of formal language theory in studies of artificial language learning: A proposal for distinguishing the differences between human and nonhuman animal learners , 2010 .

[8]  Angela D. Friederici,et al.  Artificial grammar learning meets formal language theory: an overview , 2012, Philosophical Transactions of the Royal Society B: Biological Sciences.

[9]  Tetsuro Matsuzawa,et al.  Cognition: Numerical memory span in a chimpanzee , 2000, Nature.

[10]  George A. Miller,et al.  Free Recall of Self-Embedded English Sentences , 1964, Inf. Control..

[11]  G. Boolos,et al.  The Iterative Conception of Set , 1971 .

[12]  C. Gallistel,et al.  The generative basis of natural number concepts , 2008, Trends in Cognitive Sciences.

[13]  Eric Wanner,et al.  Language acquisition: the state of the art , 1982 .

[14]  Kentaro Abe,et al.  Songbirds possess the spontaneous ability to discriminate syntactic rules , 2011, Nature Neuroscience.

[15]  C. Gallistel,et al.  Memory and the Computational Brain , 2009 .

[16]  Andreas Trotzke,et al.  Third Factors and the Performance Interface in Language Design , 2013, Biolinguistics.

[17]  S. Pinker,et al.  Natural language and natural selection , 1990, Behavioral and Brain Sciences.

[18]  G. Hitch.  The role of short-term working memory in mental arithmetic , 1978, Cognitive Psychology.

[19]  Willem H. Zuidema.  Context-freeness Revisited , 2013, CogSci.

[20]  J. Elman.  Distributed Representations, Simple Recurrent Networks, And Grammatical Structure , 1991 .

[21]  James H. Wilkinson,et al.  Turing, Alan M. , 2003 .

[22]  R. Berwick,et al.  Songs to syntax: the linguistics of birdsong , 2011, Trends in Cognitive Sciences.

[23]  Norbert Hornstein,et al.  On recursion , 2014, Front. Psychol..

[24]  A. Turing.  On Computable Numbers, with an Application to the Entscheidungsproblem. , 1937 .

[25]  Noam Chomsky,et al.  On Certain Formal Properties of Grammars , 1959, Inf. Control..

[26]  Maggie Tallerman,et al.  The Oxford Handbook of Language Evolution , 2013 .

[27]  Jeffrey Watumull,et al.  A Turing Program for Linguistic Theory , 2012, Biolinguistics.

[28]  Robert C. Berwick,et al.  Locality principles and the acquisition of syntactic knowledge , 1982 .

[29]  A. M. Turing,et al.  Solvable and Unsolvable Problems , 1954 .

[30]  S. Carey.  The Origin of Concepts , 2000 .

[31]  W. Fitch,et al.  Computational Constraints on Syntactic Processing in a Nonhuman Primate , 2004, Science.

[32]  A. Reber.  Implicit learning of artificial grammars , 1967 .

[33]  G. A. Miller,et al.  Finitary models of language users , 1963 .

[34]  Utako Minai.  Child Language Acquisition: Contrasting Theoretical Approaches , 2013 .

[35]  S. Dehaene,et al.  The Number Sense: How the Mind Creates Mathematics. , 1998 .

[36]  Timothy Q. Gentner,et al.  Recursive syntactic pattern learning by songbirds , 2006, Nature.