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Effective control of autonomous robots evolving in dynamic and unpredictable environments is a hard problem. The challenging issue is to achieve this control while the robot is performing a constrained and an interactive task. Namely, our aim is endow a mobile manipulator by controllers allowing safe and effective interactions with humans. This multi criteria optimization problem includes the coordination...
In order to facilitate online training of a robot controller composed of a spiking neural network, we propose the creation of a method dubbed a `compact evolutionary algorithm'. The compact evolutionary algorithm, derived from the compact genetic algorithm, greatly reduces the memory requirements for evolutionary optimization and also obviates the need for floating-point arithmetic capabilities allowing...
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