Sensorimotor learning in a Bayesian computational model of speech communication

Although sensorimotor exploration is a basic process within child development, clear views on the underlying computational processes remain challenging. We propose to compare eight algorithms for sensorimotor exploration, based on three components: “accommodation” performing a compromise between goal babbling and social guidance by a master, “local extrapolation” simulating local exploration of the sensorimotor space to achieve motor generalizations and “idiosyncratic babbling” which favors already explored motor commands when they are efficient. We will show that a mix of these three components offers a good compromise enabling efficient learning while reducing exploration as much as possible.