Reino Unido
Subsumption architectures are a well-known model for behaviour-based robotic control. The overall behaviour is achieved by defining a hierarchy of increasingly sophisticated behaviours. We are interested in using evolutionary algorithms to develop appropriate control architectures. We observe that the layered arrangementof behaviours in subsumption architectures are a significant obstacle to automating the development of control systems. We propose an alternative subsumption architecture inspired by the bacterial metabolism, that is more amenable to evolutionarydevelopment, where communities of simple reactive agents combine in a stochastic process to confer appropriate behaviour on the robot. We evaluate this approach by developing a traditional and a metabolic solution to a simple control problem using the e-puck educational robot.
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