| INVITED TALKS |
“Artificial Evolution of Truly Cooperative Robots”
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| Abstract Cooperation is widely spread in nature and takes several forms, ranging from behavioral coordination to sacrifice of one’s own life for the benefit of the society. This latter form of cooperation is known as “true cooperation”, or “altruism”, and is found only in few cases in nature. 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. It is thus interesting to examine under which conditions stable cooperative behavior evolves in nature and how those conditions can be translated into evolutionary algorithms that are applicable to a wide range of robots. In this talk I will quickly review biological theories of evolution of cooperative behavior and focus on the theories of kin selection and group selection. I will show how these two theories can be mapped into different evolutionary algorithms and compare their efficiency in producing neural control systems for a swarm of sugar-cube robots in a number of cooperative tasks that vary in the degree of requested cooperation. I will then describe 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. In another set of experiments I describe how those evolutionary conditions can be tested for the emergence of communication where colonies of "expressive" robots are exposed to food and danger sources that cannot be uniquely be identified at distance. Here, communication of the source type brings an advantage to the colony at the expense of the individuals that decide to tell which is the food or poison. The results shed light on the conditions that may have favored the evolution of altruistic cooperation and communication. Finally, I will describe work in progress for a real-world application of a swarm of flying robots that are expected to locate and establish an ad hoc radio network among rescuers deployed in a catastrophic scenario. The stringent mission requirements along with the unpredictable location of the rescuers on the ground made it very difficult to come up with suitable control rules. We solved the problem by using the evolutionary methods that we distilled from the previously described research in order to come up with efficient and extremely simple control systems that satisfy the basic mission requirements. *work performed in collaboration with Sara Mitri (LIS-EPFL), Sabine Hauert (LIS-EPFL), Severin Leven (LIS-EPFL), and Laurent Keller (Department of Evolutionary Biology, University of Lausanne). |