Observational Learning: Basis, Experimental Results and Models, and Implications for Robotics

In this paper, we describe a brief survey of observational learning, with particular emphasis on how this could impact on the use of observational learning in robots. We present a set of simulations of a neural model which fits recent experimental data and such that it leads to the basic idea that observational learning uses simulations of internal models to represent the observed activity, so allowing for efficient learning of the observed actions. We conclude with a set of recommendations as to how observational learning might most efficiently be used in developing and training robots for their variety of tasks.