Behaviour patterns evolution on individual and group level
Stanislav Slušný, Roman Neruda, Petra Vidnerová · Computational intelligence · 2007
In this paper we compare the evolution of simple behaviour patterns for both an individual and a group of simulated physical robots. An evolutionary algorithm with quite general objective function is used to study the ability to develop behaviour patterns such as the maze exploring ability. The group experiments demonstrate the development of collective behaviour where the group members follow the leader who is exploring the maze. Although controlled by identical simple neural network, the group members demonstrate a level of specialization. The experiments have been verified with the real physical Khepera robots.