Evolutionary computation variants for cooperative spatial coordination

This paper presents a comparative study between genetic and probabilistic search approaches of evolutionary computation. They are both applied for optimizing the behavior of multiple neural-controlled homogeneous agents whose spatial coordination tasks can only be successfully achieved through emergent cooperation. Both approaches demonstrate effective solutions of high performance; however, the genetic search approach appears to be both more robust and computationally preferred for this multi-agent case study.

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