Multi-objective Optimization of Multi-level Models for Controlling Animal Collective Behavior with Robots

Group-living animals often exhibit complex collective behaviors that emerge through the non-linear dynamics of social interactions between individuals. Previous studies have shown that it is possible to influence the collective decision-making process of groups of insects by integrating them with autonomous multi-robot systems. However, generating robot controller models for this particular task can be challenging. The main difficulties lie in accommodating group collective dynamics (macroscopic level) and agent-based models implemented in every individual robot (microscopic level). In this study, we show how such systems can be appropriately modeled, and how to use them to modulate the collective decision-making of cockroaches in a shelter-selection problem. We address two questions in this paper: first, how to optimize a microscopic model of cockroach behavior to exhibit the same collective behavior as a macroscopic model from the literature, and second, how to optimize the model describing robot behavior to modulate the collective behavior of the group of cockroaches.