Abstract
Developmental studies have suggested that infants’ action is goal-directed. When imitating an action, younger infants tend to reproduce the goal while ignoring the means (i.e., the movement to achieve the goal) whereas older infants can imitate both. We suggest that the developmental dynamics of a Recurrent Neural Network with Parametric Bias (RNNPB) may explain the mechanism of infant development. Our RNNPB model was trained to reproduce six types of actions (2 different goals x 3 different means), during which parametric biases were self-organized to represent the difference with respect to both the goal and means. Our analysis of the self-organizing process of the parametric biases revealed an infant-like developmental change in action learning: the RNNPB first adapted to the goal and then to the means. The different saliency of these two features caused this phased development. We discuss the analogy of our result to infant action development.
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Park, JC., Kim, DS., Nagai, Y. (2014). Developmental Dynamics of RNNPB: New Insight about Infant Action Development. In: del Pobil, A.P., Chinellato, E., Martinez-Martin, E., Hallam, J., Cervera, E., Morales, A. (eds) From Animals to Animats 13. SAB 2014. Lecture Notes in Computer Science(), vol 8575. Springer, Cham. https://doi.org/10.1007/978-3-319-08864-8_14
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DOI: https://doi.org/10.1007/978-3-319-08864-8_14
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