Evolutionary Explanations of Simple Communication: Signalling Games and Their Models

  • Travis LaCroixEmail author


This paper applies the theoretical criteria laid out by D’Arms et al. (1998) to various aspects of evolutionary models of signalling. The question that D’Arms et al. seek to answer can be formulated as follows: Are the models that we use to explain the phenomena in question conceptually adequate? The conceptual adequacy question relates the formal aspects of the model to those aspects of the natural world that the model is supposed to capture. Moreover, this paper extends the analysis of D’Arms et al. by asking the following additional question: Are the models that we use sufficient to explain the phenomena in question? The sufficiency question asks what formal resources are minimally required for the model to get the right results most of the time.


Signalling games Evolutionary game theory Evolutionary models Robustness Modelling 



This research was supported by the Social Sciences and Humanities Research Council of Canada, as well as a fellowship from the Department of Philosophy at Simon Fraser University. I would like to acknowledge the following people for their helpful comments and support during the writing of this paper: Nic Fillion, Matt DeVos, Holly Anderson, Jeffrey Barrett, Brian Skyrms, Louis Narens, Simon Huttegger, Cailin O’Connor, Aydin Mohseni, John Woods, Endre Begby, Gabriel Larivière, Nikolas Hamm, Sarah LaCroix. I would like to thank audiences at the IV Philogica Conference for Logic, Epistemology, and Philosophy of Science in Bogotà, Colombia and the Fall (2016) Social Dynamics Seminar at the Department of Logic and Philosophy of Science at UC Irvine. I would additionally like to thank the anonymous reviewers for extremely helpful comments and criticisms. Finally, thanks to Yoshua Bengio and the Québec AI Institute for providing generous resources.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Authors and Affiliations

  1. 1.Department of Logic and Philosophy of ScienceUniversity of CaliforniaIrvineUSA
  2. 2.Mila (Québec Artificial Intelligence Institute/Institut Québécois d’Intelligence Artificielle)MontréalCanada

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