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Bird song: a model complex adaptive system

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Abstract

Bird songs make an attractive model for studying complex systems. They may range from simple repeated sequences, to complex sequences of different phrase types, much like human language. There is probably no single way to best characterize their complexity. We should avoid saying that that “bird songs are in complexity class X”. The diversity of examples suggests that the song of one bird species or another can probably be found to exemplify and model many kinds of complex systems. We suggest that the complexity classes for cellular automata distinguished by Wolfram might give some insight into the capacity of bird songs to transmit information and of the complexity needed to generate them.

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References

  1. Brooks RA (1990) Elephants don’t play chess. Robot Auton Syst 6:3–15

    Article  Google Scholar 

  2. Okanoya K (2004) The Bengalese finch: a window on the behavioral neurobiology of birdsong syntax. Ann N Y Acad Sci 1016:724–735

    Article  Google Scholar 

  3. Weiss M, Hultsch H, Adam I, Scharff C, Kipper S (2014) The use of network analysis to study complex animal communication systems : a study on nightingale song. Proc R Soc Lond B 281:20140460

    Article  Google Scholar 

  4. Catchpole CK, Slater PJB (2003) Bird song: biological themes and variations. Cambridge University Press, New York

  5. Read AF, Weary DM (1992) The evolution of bird song: comparative analyses. Phil Trans R Soc Lond B 338:165–187

    Article  Google Scholar 

  6. Sasahara K, Cody ML, Cohen D, Taylor CE (2012) Structural design principles of complex bird songs: a network-based approach. PLoS One 7(9):e44436

    Article  Google Scholar 

  7. Sanchez, HM, Vallejo, EE and Taylor, CE (2015). PajaroLoco: a suite of programs to study the grammatical structure of bird songs. These proceedings

  8. Watts DJ, Strogatz SH (1998) Collective dynamics of “small world” networks. Nature 393:440–442

    Article  Google Scholar 

  9. Kershenbaum A et al (2014) Acoustic sequences in non-human animals: a tutorial review and prospectus. Biol Rev. doi:10.1111/brv.12160

    Google Scholar 

  10. Wolfram S (1984) Cellular automata as models of complexity. Nature 311:419–424

    Article  Google Scholar 

  11. Wolfram S (2002) A new kind of science. Wolfram Media, Champaign

    MATH  Google Scholar 

  12. Langton CG (1990) Computation at the edge of chaos. Physica D 42:12–37

    Article  MathSciNet  Google Scholar 

  13. Tan L, Alwan A, Kossan G, Cody ML, Taylor CE (2015) Dynamic time warping and sparse representation classification for birdsong phrase classification using limited training data. J Acoust Soc Am 137:1069–1080

    Article  Google Scholar 

  14. Hedley R (2015) Composition and sequential organization of song repertoires in Cassin’s Vireo (Vireo cassinii). J Ornithol. doi:10.1007/s10336-015-1238-x

    Google Scholar 

  15. Cody ML, Stabler EP, Sanchez Castellanos HM, Taylor CE (2016) Structure, syntax, and ‘small-world’ organization in the complex songs of California Thrashers (Toxostoma redivivum). Bioacoustics. doi:10.1080/09524622.2015.1089418

    Google Scholar 

  16. Kaneko K, Akutsu Y (1986) Phase transitions in two-dimensional stochastic cellular automata. J Phys A: Math Gen 19:L69–L75

    Article  MathSciNet  Google Scholar 

  17. Berwick RC, Okanoya K, Beckers GJL, Bolhuis JJ (2011) Songs to syntax: the linguistics of birdsong. Trends Cogn Sci 15:113–121

    Article  Google Scholar 

  18. Hedley R (2015) Syntactic analysis of Cassin’s Vireo songs (in review)

  19. Crutchfield JP, Feldman DP, Shalizi CR (2000) Comment on “Simple Measure for Complexity”. Phys Rev E 62:2996–2997

    Article  Google Scholar 

  20. Rothenberg D, Roeske TC, Voss HU, Naguib M, Tchernichovski O (2014) Investigation of musicality in birdsong. Hear Res 301:71–83

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by NSF Grant 1125423. We thank Richard Hedley, Carolee Caffrey, Hector Sanchez, and Julio Arriega for their assistance.

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Authors and Affiliations

  1. University of California, Los Angeles, USA

    Charles E. Taylor & Martin L. Cody

Authors
  1. Charles E. Taylor
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  2. Martin L. Cody
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Corresponding author

Correspondence to Charles E. Taylor.

Additional information

This work was presented in part at the 20th International Symposium on Artificial Life and Robotics, Beppu, Oita, Japan, January 21–23, 2015.

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Taylor, C.E., Cody, M.L. Bird song: a model complex adaptive system. Artif Life Robotics 20, 285–290 (2015). https://doi.org/10.1007/s10015-015-0231-z

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  • DOI: https://doi.org/10.1007/s10015-015-0231-z

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