Skip to main content
Log in

Attribution of Information in Animal Interaction

  • Original Article
  • Published:
Biological Theory Aims and scope Submit manuscript

Abstract

This article establishes grounds on which attributions of information and encoding in animal signals are warranted. As common interest increases between evolutionary agents, the theoretical approach best suited to describing their interaction shifts from evolutionary game theory to communication theory, which warrants informational language. The take-home positive message is that in cooperative settings, signals can appropriately be described as transmitting encoded information, regardless of the cognitive powers of signalers. The canonical example is the honeybee waggle dance, which is discussed extensively in the second and third sections. The take-home negative message is that signals are not always a consequence of coadaptation. The communication theory approach is just one end of a continuum explored more thoroughly by evolutionary game theory. The fourth and fifth sections explore this wider framework, as well as overturning some widely held misconceptions about information theory.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Notes

  1. Stegmann’s edited volume (Stegmann 2013a) characterizes the debate as between information-based and influence-based definitions. However, as pointed out by several entries in that volume, information and influence do not form a strict dichotomy. Here I am primarily concerned with establishing grounds for the attribution of information, so I make little mention of influence-based definitions.

  2. It is less clear how useful the dance is across different contexts, and the purpose for which it originally evolved. Several lines of evidence count in favor of nest site selection as the significant factor (Beekman et al. 2008; I’Anson Price and Grüter 2015). For simplicity I regretfully ignore this possibility.

  3. Haldane and Wiener knew each other personally. For some interesting remarks on their relationship, see Dronamraju’s recent biography of Haldane (Dronamraju 2017, pp. 259–260).

  4. The appropriate measure for the Gaussian distribution is presented in Shannon and Weaver (1949, p. 89). Haldane and Spurway cite Wiener (1948, p. 62) who provides a general formulation of information in a continuous distribution and does not appear to discuss the Gaussian case explicitly. For a derivation (and explanation) of the equation used by Haldane and Spurway (1954, p. 255) see Wilson (1962, Appendix).

  5. In fact the von Mises distribution would have been more appropriate (Schürch and Ratnieks 2015). The Gaussian is an acceptable approximation.

  6. The original example mentioned ants. Here and below I substitute bees without loss of generality. I retain the alphabetical labeling of types for ease of comparison with Pfeifer’s article. Space precludes discussion of model ABCD.

  7. A typo in the published version of Pfeifer (2006, p. 325) erroneously cites this value as 1.96 bits/signal.

  8. This definition has pedigree from at least two sources. First, Millikan’s definition of mapping rules between signal and world sustains the requirement of codesign and takes as a canonical example the articulation of the waggle dance (Millikan 1984, p. 107). Second, Skyrms’s account of the evolutionary emergence of conventional meaning outlines correspondences, resulting from coadaptation, between signals and the behaviors they cause (Skyrms 2010, \(\S \S\)3–5).

  9. The closest I can find to the traditional irrelevance claim is on p. 395: “Measurements of Shannon information do not necessarily reveal anything about semantic information, although they often do.”

  10. There is at least one prominent school of dissent to this orthodoxy, in the shape of the sender-receiver paradigm headed by Brian Skyrms (2010). Though Skyrms accepts that the total quantity of information in any given signal is silent on its content, he proposes a definition of information content that makes use of informational measurements (Skyrms 2010, \(\S\)3). Importantly, it does not cut between signals and cues. Like ORR’s definition of Shannon information, it is defined in terms of probabilities, not function. In what follows I leave the Skyrms account to one side. Though it is useful and innovative, there is a much more direct way to demonstrate the relationship between information in MCT and meaning in biological signals.

  11. “Subpersonal” is applied to brain states that are not assumed to play a role in conscious thought. I use it here as a modifier to “content” that makes no assumptions further than codesign of signalers and receivers. It is therefore applicable to subcognitive and noncognitive systems in the manner of Shea (2007) and Millikan (2013).

  12. Measured in bits per symbol, not per second.

  13. Oliver Lean has made the same point (Lean 2016, pp. 239–240).

  14. Signals with this dual character were labeled “neutral” by Lewis (1969), “pushmi-pullyu” by Millikan (1995) and “primitive” by Harms (2004). The latter is the preferred term. Incidentally, it might be thought that the instruction/information distinction is just another way of describing the influence/information distinction. Unfortunately, the latter is far more ambiguous.

  15. The distinction between code-as-correspondence and code-as-redundancy mirrors a well-known duality in communication theory between data compression (“source coding”) and data transmission (“channel coding”). Speculatively, the selective pressures on animal communication may be skewed far more towards solving the latter problem. Hailman’s book (Hailman 2008) and Wiley’s essays (Wiley 1983, 2013) are examples.

  16. Though see Bergstrom and Lachmann (2003) for conditions under which the slower-evolving organism enjoys the benefit, a phenomenon they call the Red King effect.

References

  • Bar-Hillel Y, Carnap R (1953) Semantic information. Br J Philos Sci 4(14):147–157

    Article  Google Scholar 

  • Beekman M, Gloag RS, Even N et al (2008) Dance precision of Apis florea—clues to the evolution of the honeybee dance language? Behav Ecol Sociobiol 62(8):1259–1265

    Article  Google Scholar 

  • Beekman M, Makinson JC, Couvillon MJ et al (2015) Honeybee linguistics—a comparative analysis of the waggle dance among species of Apis. Front Ecol Evol 3:11

    Article  Google Scholar 

  • Bergstrom CT, Lachmann M (2003) The red king effect: when the slowest runner wins the coevolutionary race. Proc Natl Acad Sci USA 100(2):593–598

    Article  Google Scholar 

  • Biesmeijer JC, Seeley TD (2005) The use of waggle dance information by honey bees throughout their foraging careers. Behav Ecol Sociobiol 59(1):133–142

    Article  Google Scholar 

  • Brusse C, Bruner J (2017) Responsiveness and robustness in the David Lewis signaling game. Philos Sci 84(5):1068–1079

    Article  Google Scholar 

  • Chittka L (2004) Dances as windows into insect perception. PLoS Biol 2(7):898–900

    Article  Google Scholar 

  • Danforth B (2007) Bees. Curr Biol 17(5):R156–R161

    Article  Google Scholar 

  • Dawkins R, Krebs JR (1978) Animal signals: information or manipulation? In: Krebs JR, Davies NB (eds) Behavioural ecology: an evolutionary approach, 1st edn. Wiley, Hoboken, pp 282–309

    Google Scholar 

  • Dennett DC (1983) Intentional systems in cognitive ethology: the “Panglossian paradigm” defended. Behav Brain Sci 6(3):343–355

    Article  Google Scholar 

  • Dretske F (1983) Précis of Knowledge and the Flow of Information. Behav Brain Sci 6(1):55–63

    Article  Google Scholar 

  • Dronamraju KR (2017) Popularizing science: the life and work of JBS Haldane. Oxford University Press, New York

    Google Scholar 

  • Godfrey-Smith P (2013) Signals, icons, and beliefs. In: Ryder D, Kingsbury J, Williford K (eds) Millikan and her critics. Wiley, Hoboken, pp 41–58

    Google Scholar 

  • Godfrey-Smith P, Sterelny K (2016) Biological information. In: Zalta EN (ed) The Stanford encyclopedia of philosophy. Summer 2016 edition. Stanford University, Stanford

    Google Scholar 

  • Gould JL (1975) Honey bee recruitment: the dance-language controversy. Science 189(4204):685–693

    Article  Google Scholar 

  • Hailman JP (2008) Coding and redundancy: man-made and animal-evolved signals. Harvard University Press, Cambridge

    Google Scholar 

  • Haldane JBS, Spurway H (1954) A statistical analysis of communication in “Apis mellifera” and a comparison with communication in other animals. Insect Soc 1(3):247–283

    Article  Google Scholar 

  • Harms WF (2004) Primitive content, translation, and the emergence of meaning in animal communication. In: Oller DK, Griebel U (eds) Evolution of communication systems: a comparative approach. MIT Press, Cambridge, pp 31–48

    Google Scholar 

  • Hurd PL, Enquist M (2005) A strategic taxonomy of biological communication. Anim Behav 70(5):1155–1170

    Article  Google Scholar 

  • I’Anson Price R, Grüter C (2015) Why, when and where did honey bee dance communication evolve? Front Ecol Evol 3:125

    Google Scholar 

  • Iglesias PA (2016) The use of rate distortion theory to evaluate biological signaling pathways. IEEE Trans Mol Biol Multi-Scale Commun 2(1):31–39

    Article  Google Scholar 

  • Kalkman D (2017) Information, influence, and the causal-explanatory role of content in understanding receiver responses. Biol Philos 32(6):1127–1150

    Article  Google Scholar 

  • Krebs JR, Dawkins R (1984) Animal signals: mind-reading and manipulation. In: Krebs JR, Davies NB (eds) Behavioural ecology: an evolutionary approach, 2nd edn. Blackwell Scientific, Oxford, pp 380–402

    Google Scholar 

  • Lean O (2016) Biological information. PhD thesis, University of Bristol, Bristol

  • Lewis D (1969) Convention: a philosophical study. Blackwell, Oxford

    Google Scholar 

  • Martínez M, Godfrey-Smith P (2016) Common interest and signaling games: a dynamic analysis. Philos Sci 83(3):371–392

    Article  Google Scholar 

  • Millikan RG (1984) Language, thought, and other biological categories. MIT Press, Cambridge

    Google Scholar 

  • Millikan RG (1995) Pushmi–Pullyu representations. Philos Perspect 9:185–200

    Article  Google Scholar 

  • Millikan RG (2013) Natural information, intentional signs and animal communication. In: Stegmann UE (ed) Animal communication theory. Cambridge University Press, New York, pp 133–146

    Chapter  Google Scholar 

  • Morton ES, Coss RG (2013) Mitogenic rays and the information metaphor: transmitted information has had its day. In: Stegmann U (ed) Animal communication theory. Cambridge University Press, New York, pp 207–231

    Chapter  Google Scholar 

  • Nakano T, Eckford AW, Haraguchi T (2013) Molecular communication. Cambridge University Press, New York

    Book  Google Scholar 

  • Owren MJ, Rendall D, Ryan MJ (2010) Redefining animal signaling: influence versus information in communication. Biol Philos 25(5):755–780

    Article  Google Scholar 

  • Pfeifer J (2006) The use of information theory in biology: lessons from social insects. Biol Theor 1(3):317–330

    Article  Google Scholar 

  • Preece K, Beekman M (2014) Honeybee waggle dance error: adaption or constraint? Unravelling the complex dance language of honeybees. Anim Behav 94:19–26

    Article  Google Scholar 

  • Reading A (2011) Meaningful information, volume 1 of Springer briefs in biology. Springer, New York

    Book  Google Scholar 

  • Reddy MJ (1979) The conduit metaphor: a case of frame conflict in our language about language. In: Ortony A (ed) Metaphor and thought. Cambridge University Press, Cambridge, pp 254–83

    Google Scholar 

  • Rendall D, Owren MJ (2013) Communication without meaning or information: abandoning language-based and informational constructs in animal communication theory. In: Stegmann U (ed) Animal communication theory. Cambridge University Press, New York, pp 151–188

    Chapter  Google Scholar 

  • Rendall D, Owren MJ, Ryan MJ (2009) What do animal signals mean? Anim Behav 78(2):233–240

    Article  Google Scholar 

  • Reznikova Z (2017) Studying animal languages without translation: an insight from ants. Springer, New York

    Book  Google Scholar 

  • Riley JR, Greggers U, Smith AD et al (2005) The flight paths of honeybees recruited by the waggle dance. Nature 435(7039):205–207

    Article  Google Scholar 

  • Ryan MJ (2013) The importance of integrative biology to sexual selection and communication. In: Stegmann U (ed) Animal communication theory. Cambridge University Press, New York, pp 233–255

    Chapter  Google Scholar 

  • Sarkar S (2013) Information in animal communication: when and why does it matter? In: Stegmann UE (ed) Animal communication theory. Cambridge University Press, New York, pp 189–205

    Chapter  Google Scholar 

  • Schürch R, Ratnieks FLW (2015) The spatial information content of the honey bee waggle dance. Behav Evol Ecol 3:22

    Google Scholar 

  • Shannon CE (1948a) A mathematical theory of communication (part 1). Bell Syst Tech J 27(3):379–423

    Article  Google Scholar 

  • Shannon CE (1948b) A mathematical theory of communication (part 2). Bell Sys Tech J 27(4):623–656

    Article  Google Scholar 

  • Shannon CE, Weaver W (1949) The mathematical theory of communication. University of Illinois Press, Urbana

    Google Scholar 

  • Shea N (2007) Consumers need information: supplementing teleosemantics with an input condition. Philos Phenomenol Res 75(2):404–435

    Article  Google Scholar 

  • Skyrms B (2010) Signals: evolution, learning, and information. Oxford University Press, Oxford

    Book  Google Scholar 

  • Stegmann UE (ed) (2013a) Animal communication theory: information and influence. Cambridge University Press, New York

    Google Scholar 

  • Stegmann UE (2013b) On the ‘transmission sense of information.’ Biol Philos 28(1):141–144

    Article  Google Scholar 

  • von Frisch K (1948) Gelöste und ungelöste Rätsel der Bienensprache. Naturwissenschaften 35:38–43

    Article  Google Scholar 

  • von Frisch K (1950) Bees: their vision, chemical senses, and language. Cornell University Press, Ithaca

    Google Scholar 

  • von Frisch K (1952) Die wechselseitigen Beziehungen und die Harmonie im Bienenstaat. Number XXXIV in Colloques Internationaux du CNRS, Paris, pp 271–292

  • Wagner EO (2012) Deterministic chaos and the evolution of meaning. Br J Philos Sci 63(3):547–575

    Article  Google Scholar 

  • Wagner EO (2015) Conventional semantic meaning in signalling games with conflicting interests. Br J Philos Sci 66(4):751–773

    Article  Google Scholar 

  • Wiener N (1948) Cybernetics; or, control and communication in the animal and the machine, 2nd edn. MIT Press, Cambridge

    Google Scholar 

  • Wiley RH (1983) The evolution of communication: information and manipulation. In: Halliday T, Slater PJB (eds) Animal behaviour: communication, vol 2. Blackwell Scientific Publications, Oxford, pp 156–189

    Google Scholar 

  • Wiley RH (2013) Communication as a transfer of information: measurement, mechanism and meaning. In: Stegmann U (ed) Animal communication theory. Cambridge University Press, New York, pp 113–132

    Chapter  Google Scholar 

  • Wilson EO (1962) Chemical communication among workers of the fire ant Solenopsis saevissima (Fr. Smith) 2. An information analysis of the odour trail. Anim Behav 10(1–2):148–158

    Article  Google Scholar 

Download references

Acknowledgements

Thanks are due to Jessica Pfeifer, Justin Bruner, Ron Planer, and two anonymous referees for comments on earlier drafts, and to Siva Kalyan for assistance with diagrams. Thanks also to audiences at the 2017 Sydney-ANU philosophy of biology workshop and the University of Sydney Social Insects lab, especially Madeleine Beekman and Isobel Ronai. This research is supported by an Australian Government Research Training Program (RTP) Scholarship and Australian Research Council Laureate Fellowship Grant FL130100141.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Stephen Francis Mann.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mann, S.F. Attribution of Information in Animal Interaction. Biol Theory 13, 164–179 (2018). https://doi.org/10.1007/s13752-018-0299-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13752-018-0299-5

Keywords

Navigation