title: Modeling collective animal behavior with a cognitive perspective: a methodological framework.
abstract: The last decades have seen an increasing interest in modeling collective animal behavior. Some studies try to reproduce as accurately as possible the collective dynamics and patterns observed in several animal groups with biologically plausible, individual behavioral rules. The objective is then essentially to demonstrate that the observed collective features may be the result of self-organizing processes involving quite simple individual behaviors. Other studies concentrate on the objective of establishing or enriching links between collective behavior researches and cognitive or physiological ones, which then requires that each individual rule be carefully validated. Here we discuss the methodological consequences of this additional requirement. Using the example of corpse clustering in ants, we first illustrate that it may be impossible to discriminate among alternative individual rules by considering only observational data collected at the group level. Six individual behavioral models are described: They are clearly distinct in terms of individual behaviors, they all reproduce satisfactorily the collective dynamics and distribution patterns observed in experiments, and we show theoretically that it is strictly impossible to discriminate two of these models even in the limit of an infinite amount of data whatever the accuracy level. A set of methodological steps are then listed and discussed as practical ways to partially overcome this problem. They involve complementary experimental protocols specifically designed to address the behavioral rules successively, conserving group-level data for the overall model validation. In this context, we highlight the importance of maintaining a sharp distinction between model enunciation, with explicit references to validated biological concepts, and formal translation of these concepts in terms of quantitative state variables and fittable functional dependences. Illustrative examples are provided of the benefits expected during the often long and difficult process of refining a behavioral model, designing adapted experimental protocols and inversing model parameters.
authors: Université de Toulouse, UPS, INPT, LAPLACE, Laboratoire Plasma et Conversion d'Energie, Toulouse, France. weitz@laplace.univ-tlse.fr
authors: Sebastian
authors: S
authors: Weitz
authors: Stéphane
authors: S
authors: Blanco
authors: Richard
authors: R
authors: Fournier
authors: Jacques
authors: J
authors: Gautrais
authors: Christian
authors: C
authors: Jost
authors: Guy
authors: G
authors: Theraulaz
mesh_terms: D000818:Animals; D001000:Ants / Q000502:physiology*; D001522:Behavior, Animal / Q000502:physiology*; D002102:Cadaver; D002755:Choice Behavior; D003071:Cognition; D003657:Decision Making / Q000502:physiology*; D004777:Environment; D008954:Models, Biological; D015233:Models, Statistical; D012919:Social Behavior