MOTION RULES AND TECHNICAL DETAILS OF THE AGENT-BASED MODEL FOR ANT FORAGING from Variability in individual activity bursts improves ant foraging success
2016-12-02T11:33:21Z (GMT) by
Using experimental and computational methods, we study the role of behavioural variability in activity bursts (or temporal activity patterns) for individual and collective regulation of foraging in <i>A. senilis</i> ants. First, foraging experiments were carried out under special conditions (low densities of ants and food and absence of external cues or stimuli) where individual-based strategies are most prevalent. By using marked individuals and recording all foraging trajectories, we were then able to precisely quantify behavioural variability among individuals. Our main conclusions are that (i) variability of ant trajectories (turning angles, speed, etc.) is low compared with variability of temporal activity profiles, and (ii) this variability seems to be driven by plasticity of individual behavioural through time, rather than the presence of fixed behavioural stereotypes or specialists within the group. The statistical measures obtained from these experimental foraging patterns are then used to build a general agent-based model (ABM) which includes the most relevant properties of ant foraging under natural conditions, including recruitment through pheromone communication. Using the ABM, we are able to provide computational evidence that the characteristics of individual variability observed in our experiments can provide a functional advantage (in terms of foraging success) to the group; thus, we propose the biological basis underpinning our observations. Altogether, our study reveals the potential utility of experiments under simplified (laboratory) conditions for understanding information-gathering in biological systems.