We introduce FARSA, an open-source Framework for Autonomous Robotics Simulation and Analysis, that allows us to easily set up and carry on adaptive experiments involving complex robot/environmental models. Moreover, we show how a simulated iCub robot can be trained, through an evolutionary algorithm, to display reaching and integrated reaching and grasping behaviours. The results demonstrate how the use of an implicit selection criterion, estimating the extent to which the robot is able to produce the expected outcome without specifying the manner through which the action should be realized, is sufficient to develop the required capabilities despite the complexity of the robot and of the task.
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