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A game theoretical approach to the evolution of structured communication codes

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Abstract

Structured meaning-signal mappings, i.e., mappings that preserve neighborhood relationships by associating similar signals with similar meanings, are advantageous in an environment where signals are corrupted by noise and sub-optimal meaning inferences are rewarded as well. The evolution of these mappings, however, cannot be explained within a traditional language evolutionary game scenario in which individuals meet randomly because the evolutionary dynamics is trapped in local maxima that do not reflect the structure of the meaning and signal spaces. Here we use a simple game theoretical model to show analytically that when individuals adopting the same communication code meet more frequently than individuals using different codes—a result of the spatial organization of the population—then advantageous linguistic innovations can spread and take over the population. In addition, we report results of simulations in which an individual can communicate only with its K nearest neighbors and show that the probability that the lineage of a mutant that uses a more efficient communication code becomes fixed decreases exponentially with increasing K. These findings support the mother tongue hypothesis that human language evolved as a communication system used among kin, especially between mothers and offspring.

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References

  • Abbott B (2000) Fodor and Lepore on meaning similarity and compositionality. J Philos 97:454–455

    Article  Google Scholar 

  • Allee WC (1931) Animal aggregations. A study in general sociology. University of Chicago Press, Chicago

    Google Scholar 

  • Brighton H, Smith K, Kirby S (2005) Language as an evolutionary system. Phys Life Rev 2:177–226

    Article  Google Scholar 

  • Cangelosi A (2001) Evolution of communication and language using signals, symbols, and words. IEEE Trans Evol Comput 5:93–101

    Article  Google Scholar 

  • Cavalli-Sforza LL, Feldman MW (1983) Paradox of the evolution of communication and of social interactivity. Proc Natl Acad Sci USA 80:2017–2021

    Article  PubMed  CAS  Google Scholar 

  • Chomsky N (1972) Language and mind. Harcourt Brace Jovanovich, New York

    Google Scholar 

  • Churchland PM (1998) Conceptual similarity across sensory and neural diversity: the Fodor/Lepore challenge answered. J Philos 95:5–32

    Article  Google Scholar 

  • Courchamp F, Clutton-Brock T, Grenfell B (1999) Inverse density dependence and the Allee effect. Trends Ecol Evol 14:405–410

    Article  PubMed  Google Scholar 

  • Dawkins R, Krebs JR (1978) Animal signals: information or manipulation? In: Krebs JR, Davies NB (eds) Behavioural ecology: an evolutionary approach. Blackwel, Oxford, pp 282–309

    Google Scholar 

  • Deacon TW (1997) The symbolic species. W.W. Norton & Company, New York

    Google Scholar 

  • de Saussure F (1966) Course in general linguistics. Translated by Wade Baskin. McGraw-Hill, New York

    Google Scholar 

  • Dunbar R (1996) Grooming, gossip, and the evolution of language. Harvard University Press, Cambridge

    Google Scholar 

  • Eshel I, Cavalli-Sforza LL (1982) Assortement of encounters and evolution of cooperativeness. Proc Natl Acad Sci USA 79:1331–1335

    Article  PubMed  Google Scholar 

  • Ewens WJ (2004) Mathematical population genetics, 2nd edn. Springer, New York

    Google Scholar 

  • Fitch WT (2004) Kin selection and mother tongues: a neglected component in language evolution. In: Oller K, Griebel U (eds) Evolution of communication systems: a comparative approach. MIT Press, Cambridge, pp 275–296

    Google Scholar 

  • Fodor J (1983) The modularity of mind. MIT Press, Cambridge

    Google Scholar 

  • Fodor J, Lepore E (1999) All at sea in semantic space: Churchland on meaning similarity. J Philos 96:381–403

    Article  Google Scholar 

  • Fontanari JF, Perlovsky LI (2007) Evolving compositionality in evolutionary language games. IEEE Trans Evol Comput 11:758–769

    Article  Google Scholar 

  • Fudenberg D, Tirole J (1991) Game theory. MIT Press, Cambridge

    Google Scholar 

  • Gordon P (2004) Numerical cognition without words: evidence from Amazonia. Science 306:496–499

    Article  PubMed  CAS  Google Scholar 

  • Hurford JR (1989) Biological evolution of the Saussurean sign as a component of the language acquisition device. Lingua 77:187–222

    Article  Google Scholar 

  • Kinzler KD, Dupoux E, Spelke ES (2007) The native language of social cognition. Proc Natl Acad Sci USA 104:12577–12580

    Article  PubMed  CAS  Google Scholar 

  • Maynard Smith J (1982) Evolution and the theory of games. Cambridge University Press, Cambridge

    Google Scholar 

  • Michod RE (1995) Eros and evolution: a natural philosophy of sex. Addison-Wesley, Reading

    Google Scholar 

  • Mitchell M (1996) An introduction to genetic algorithms. MIT Press, Cambridge

    Google Scholar 

  • Nettle D (1999) Linguistic diversity. Oxford University Press, Oxford

    Google Scholar 

  • Noble J (2000) Cooperation, competition and the evolution of prelinguistic communication. In: Knight C, Studdert-Kennedy M, Hurford J (eds) The evolutionary emergence of language. Cambridge University Press, Cambridge, pp 40–61

    Google Scholar 

  • Nowak MA, Krakauer DC (1999) The evolution of language. Proc Natl Acad Sci USA 96:8028–8033

    Article  PubMed  CAS  Google Scholar 

  • Nowak MA, Plotkin JB, Krakauer DC (1999) The evolutionary language game. J Theor Biol 200:147–162

    Article  PubMed  CAS  Google Scholar 

  • Nowak MA, Komarova NL, Niyogi P (2002) Computational and evolutionary aspects of language. Nature 417:611–617

    Article  PubMed  CAS  Google Scholar 

  • Nowak MA, Sasaki A, Taylor C, Fudenberg D (2004) Emergence of cooperation and evolutionary stability in finite populations. Nature 428:646–650

    Article  PubMed  CAS  Google Scholar 

  • Oliphant M (1996) The dilemma of Saussurean communication. Biosystems 37:31–38

    Article  PubMed  CAS  Google Scholar 

  • Patriarca M, Leppanen T (2004) Modeling language competition. Phys A 338:296–299

    Article  Google Scholar 

  • Pawlowitsch C (2007) Finite populations choose an optimal language. Available at http://homepage.univie.ac.at/christina.pawlowitsch/4-finite-populations-language-game-2.pdf (Unpublished)

  • Perlovsky LI (2006) Fuzzy dynamic logic. New Math Nat Comp 2:43–55

    Article  Google Scholar 

  • Perlovsky LI (2007) Evolution of languages, consciousness, and cultures. IEEE Comput Intell Soc Mag 2:25–39

    Article  Google Scholar 

  • Petitto LA (1994) Language in the prelinguistic child. In: Bloom P (ed) Language acquisition: core readings. MIT/Bradford Press, Cambridge

    Google Scholar 

  • Pinker S (1994) The language instinct. Penguin Press, London

    Google Scholar 

  • Pinker S, Bloom P (1990) Natural language and natural selection. Behav Brain Sci 13:707–784

    Google Scholar 

  • Radick G (2002) Darwin on language and selection. Selection 3:7–16

    Article  Google Scholar 

  • Reidys CM, Stadler PF (2001) Neutrality in fitness landscapes. Appl Math Comp 117:321-350

    Article  Google Scholar 

  • Schuster P, Stadler PF (2002) Networks in molecular evolution. Complexity 8:34–42

    Article  Google Scholar 

  • Seyfarth RM, Cheney DL, Marler P (1980) Monkey responses to three different alarm calls: evidence of predator classification and semantic classification. Science 210:801–803

    Article  PubMed  CAS  Google Scholar 

  • Smith K, Kirby S, Brighton H (2003) Iterated learning: a framework for the emergence of language. Artif Life 9:371–386

    Article  PubMed  Google Scholar 

  • Wright S (1921) Systems of mating. III. Assortative mating based on somatic resemblance. Genetics 6:144–161

    PubMed  CAS  Google Scholar 

  • Zahavi A (1975) Mate selection: a selection for a handicap. J Theor Biol 53:205–214

    Article  PubMed  CAS  Google Scholar 

  • Zahavi A (1993) The fallacy of conventional signalling. Proc R Soc Lond B 340:227–230

    CAS  Google Scholar 

  • Zuidema W (2003) Optimal communication in a noisy and heterogeneous environment. Lect Notes Artif Intell 2801:53–563

    Google Scholar 

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Acknowledgments

This work was supported in part by the Air Force Office of Scientific Research, Air Force Material Command, USAF, under grant number FA9550-06-1-0202, and in part by CNPq and FAPESP, Project No. 04/06156-3. The US Government is authorized to reproduce and distribute reprints for Governmental purpose notwithstanding any copyright notation thereon.

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Correspondence to José F. Fontanari.

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Fontanari, J.F., Perlovsky, L.I. A game theoretical approach to the evolution of structured communication codes. Theory Biosci. 127, 205–214 (2008). https://doi.org/10.1007/s12064-008-0024-1

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