Keynote Talk 2

Summary form only given. Truly cooperative robots would be very useful in conditions where unpredictable events in the mission may require a cost by one or more individual robots for the success of the entire mission. However, the interactions among robots sharing the same environment can affect in unexpected ways the behavior of individual robots, making very difficult the design of rules that produce stable cooperative behavior. In this article, the author reviews biological theories of evolution of cooperative behavior and focus on the theories of kin selection and group selection. The author shows how these two theories can be mapped into different evolutionary algorithms and compare their efficiency in producing control systems for a swarm of sugar-cube robots in a number of cooperative tasks that vary in the degree of requested cooperation. The author then describes an example where the most efficient algorithm is used to evolve a control system for a swarm of aerial robots that must establish a radio network between persons on the ground.