Socially guided intrinsically motivated learner

This paper studies the coupling of two learning strategies: internally guided learning and social interaction. We present Socially Guided Intrinsic Motivation by Demonstration (SGIM-D) and its interactive learner version Socially Guided Intrinsic Motivation with Interactive learning at the Meta level (SGIM-IM), which are algorithms for learning inverse models in high dimensional continuous sensorimotor spaces. After describing the general framework of our algorithms, we illustrate with a fishing experiment.