title: Modeling warfare in social animals: a "chemical" approach.
abstract: We present here a general method for modelling the dynamics of battles among social animals. The proposed method exploits the procedures widely used to model chemical reactions, but still uncommon in behavioural studies. We applied this methodology to the interpretation of experimental observations of battles between two species of ants (Lasius neglectus and Lasius paralienus), but this scheme may have a wider applicability and can be extended to other species as well. We performed two types of experiment labelled as interaction and mortality. The interaction experiments are designed to obtain information on the combat dynamics and lasted one hour. The mortality ones provide information on the casualty rates of the two species and lasted five hours. We modelled the interactions among ants using a chemical model which considers the single ant individuals and fighting groups analogously to atoms and molecules. The mean-field behaviour of the model is described by a set of non-linear differential equations. We also performed stochastic simulations of the corresponding agent-based model by means of the Gillespie event-driven integration scheme. By fitting the stochastic trajectories with the deterministic model, we obtained the probability distribution of the reaction parameters. The main result that we obtained is a dominance phase diagram, that gives the average trajectory of a generic battle, for an arbitrary number of opponents. This phase diagram was validated with some extra experiments. With respect to other war models (e.g., Lanchester's ones), our chemical model considers all phases of the battle and not only casualties. This allows a more detailed description of the battle (with a larger number of parameters), allowing the development of more sophisticated models (e.g., spatial ones), with the goal of distinguishing collective effects from the strategic ones.
authors.affiliation: Department of Information Engineering, University of Florence, Firenze, Italy; Center for the Study of Complex Dynamics (CSDC), University of Florence, Sesto Fiorentino (FI), Italy.
authors.forename: Alisa
authors.initials: A
authors.lastname: Santarlasci
authors.affiliation: Department Physics and Astronomy, University of Florence, Sesto Fiorentino (FI), Italy; Center for the Study of Complex Dynamics (CSDC), University of Florence, Sesto Fiorentino (FI), Italy.
authors.forename: Gianluca
authors.initials: G
authors.lastname: Martelloni
authors.affiliation: Department of Biology, University of Florence, Sesto Fiorentino (FI), Italy.
authors.forename: Filippo
authors.initials: F
authors.lastname: Frizzi
authors.affiliation: Department of Biology, University of Florence, Sesto Fiorentino (FI), Italy.
authors.forename: Giacomo
authors.initials: G
authors.lastname: Santini
authors.affiliation: Department Physics and Astronomy, University of Florence, Sesto Fiorentino (FI), Italy; Center for the Study of Complex Dynamics (CSDC), University of Florence, Sesto Fiorentino (FI), Italy; National Institute of Nuclear Physics (INFN), sez. Firenze, Italy.
authors.forename: Franco
authors.initials: F
authors.lastname: Bagnoli
mesh_terms: D000374:Aggression; D000818:Animals; D001000:Ants / Q000502:physiology; D001522:Behavior, Animal; D003198:Computer Simulation; D008954:Models, Biological; D011336:Probability; D013269:Stochastic Processes