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In this paper, we show how a simulated humanoid robot controlled by an artificial neural network can acquire the ability to manipulate spherical objects located over a table by reaching, grasping, and lifting them. The robot controller is developed through an adaptive process in which the free parameters encode the control rules that regulate the fine-grained interaction between the agent and the environment, and the variations of these free parameters are retained or discarded on the basis of their effects at the level of the behavior exhibited by the agent. The robot develops the sensory-motor coordination required to carry out the task in two different conditions; that is, with or without receiving as input a linguistic instruction that specifies the type of behavior to be exhibited during the current phase. The obtained results shown that the linguistic instructions facilitate the development of the required behavioral skills.
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Massera et al. (2010) studied this question.
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