On the evolution of self-organised role-allocation and role-switching behaviour in swarm robotics: a case study

In spite of its significance for the adaptability of autonomous robotic swarms, the dynamic allocation and re-distribution of robots to tasks (i.e., role-allocation and role-switching behaviour) is still a design challenge in swarm robotics. This study investigates a simulated foraging scenario in which the variability of the environmental conditions requires that robots switch between two roles (i.e., foraging and nestpatrolling). To the best of our knowledge, this is the first simulation study that demonstrates that role-allocation and role-switching behaviour can be evolved using dynamic neural network controllers for robots with minimal communication capabilities. Initial analyses of the best evolved teams shed light on some of the characteristics and robustness of the strategies used by these teams to repeatedly face this task.