Literature DB >> 8924637

The dilemma of Saussurean communication.

M Oliphant1.   

Abstract

A Saussurean communication system exists when an entire communicating population uses a single 'language' that maps states unambiguously onto symbols and then back into the original states. This paper describes a number of simulations performed with a genetic algorithm to investigate the conditions necessary for such communication systems to evolve. The first simulation shows that Saussurean communication evolves in the simple case where direct selective pressure is placed on individuals to be both good transmitters and good receivers. The second simulation demonstrates that, in the more realistic case where selective pressure is only placed on doing well as a receiver, Saussurean communication fails to evolve. Two methods, inspired by research on the Prisoner's Dilemma, are used to attempt to solve this problem. The third simulation shows that, even in the absence of selective pressure on transmission, Saussurean communication can evolve if individuals interact multiple times with the same communication partner and are given the ability to respond differentially based on past interaction. In the fourth simulation, spatially organized populations are used, and it is shown that this allows Saussurean communication to evolve through kin selection.

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Year:  1996        PMID: 8924637     DOI: 10.1016/0303-2647(95)01543-4

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  8 in total

1.  Cost and conflict in animal signals and human language.

Authors:  M Lachmann; S Szamado; C T Bergstrom
Journal:  Proc Natl Acad Sci U S A       Date:  2001-10-30       Impact factor: 11.205

2.  Common language or Tower of Babel? On the evolutionary dynamics of signals and their meanings.

Authors:  Minus van Baalen; Vincent A A Jansen
Journal:  Proc Biol Sci       Date:  2003-01-07       Impact factor: 5.349

3.  A game theoretical approach to the evolution of structured communication codes.

Authors:  José F Fontanari; Leonid I Perlovsky
Journal:  Theory Biosci       Date:  2008-03-07       Impact factor: 1.919

4.  Words as alleles: connecting language evolution with Bayesian learners to models of genetic drift.

Authors:  Florencia Reali; Thomas L Griffiths
Journal:  Proc Biol Sci       Date:  2009-10-07       Impact factor: 5.349

5.  The evolution of language.

Authors:  M A Nowak; D C Krakauer
Journal:  Proc Natl Acad Sci U S A       Date:  1999-07-06       Impact factor: 11.205

6.  Simulating the real origins of communication.

Authors:  Richard A Blythe; Thomas C Scott-Phillips
Journal:  PLoS One       Date:  2014-11-26       Impact factor: 3.240

Review 7.  Minimal Requirements for the Emergence of Learned Signaling.

Authors:  Matthew Spike; Kevin Stadler; Simon Kirby; Kenny Smith
Journal:  Cogn Sci       Date:  2016-03-14

8.  Emergence of linguistic conventions in multi-agent reinforcement learning.

Authors:  Dorota Lipowska; Adam Lipowski
Journal:  PLoS One       Date:  2018-11-29       Impact factor: 3.240

  8 in total

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