From Solitary to Collective Behaviours: Decision Making and Cooperation

In a social scenario, establishing whether a collaboration is required to achieve a certain goal is a complex problem that requires decision making capabilities and coordination among the members of the group. Depending on the environmental contingencies, solitary actions may result more efficient than collective ones and vice versa. In robotics, it may be difficult to estimate the utility of engaging in collaboration versus remaining solitary, especially if the robots have only limited knowledge about the environment. In this paper, we use artificial evolution to synthesise neural controllers that let a homogeneous group of robots decide when to switch from solitary to collective actions based on the information gathered through time. However, being in a social scenario, the decision taken by a robot can influence--and is influenced itself--by the status of the other robots that are taking their own decisions at the same time. We show that the simultaneous presence of robots trying to decide whether to engage in a collective action or not can lead to cooperation in the decision making process itself.