The consequences of Zipf's law for syntax and symbolic reference

Although many species possess rudimentary communication systems, humans seem to be unique with regard to making use of syntax and symbolic reference. Recent approaches to the evolution of language formalize why syntax is selectively advantageous compared with isolated signal communication systems, but do not explain how signals naturally combine. Even more recent work has shown that if a communication system maximizes communicative efficiency while minimizing the cost of communication, or if a communication system constrains ambiguity in a non-trivial way while a certain entropy is maximized, signal frequencies will be distributed according to Zipf's law. Here we show that such communication principles give rise not only to signals that have many traits in common with the linking words in real human languages, but also to a rudimentary sort of syntax and symbolic reference.

[1]  M. Donald.  Origins of the modern mind , 1991 .

[2]  Reinhard Köhler,et al.  Patterns in syntactic dependency networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[3]  Charles F. Hockett,et al.  Logical considerations in the study of animal communication , 1960 .

[4]  S. Grossberg,et al.  Neural network models of categorical perception , 2000, Perception & psychophysics.

[5]  George Kingsley Zipf,et al.  Human behavior and the principle of least effort , 1949 .

[6]  M A Nowak,et al.  The evolution of language. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Wentian Li,et al.  Random texts exhibit Zipf's-law-like word frequency distribution , 1992, IEEE Trans. Inf. Theory.

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

[9]  T. Deacon.  The Symbolic Species: The Co-evolution of Language and the Brain , 1998 .

[10]  Daniel Dominic Sleator,et al.  Parsing English with a Link Grammar , 1995, IWPT.

[11]  Ramon Ferrer i Cancho,et al.  Decoding least effort and scaling in signal frequency distributions , 2005 .

[12]  Béla Bollobás,et al.  Modern Graph Theory , 2002, Graduate Texts in Mathematics.

[13]  George Kingsley Zipf,et al.  Human Behaviour and the Principle of Least Effort: an Introduction to Human Ecology , 2012 .

[14]  Ricard V. Solé,et al.  Least effort and the origins of scaling in human language , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Yuen Ren Chao,et al.  Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology , 1950 .

[16]  Martin A. Nowak,et al.  The evolution of syntactic communication , 2000, Nature.

[17]  David G. Hays,et al.  Uniquely human: The evolution of speech, thought, and selfless behavior , 1992 .

[18]  M A Nowak,et al.  An error limit for the evolution of language , 1999, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[19]  Noam Chomsky,et al.  वाक्यविन्यास का सैद्धान्तिक पक्ष = Aspects of the theory of syntax , 1965 .

[20]  R. Harald Baayen,et al.  Word Frequency Distributions , 2001 .

[21]  Gerhard Helbig.  Probleme der Valenz- und Kasustheorie , 1992 .

[22]  M A Nowak,et al.  Evolutionary biology of language. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[23]  M. Studdert-Kennedy,et al.  Approaches To The Evolution Of Language: Social And Cognitive Bases , 1998 .

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