intrinsic motivation systems for autonomous mental development
Author(s): Pierre-Yves Oudeyer, Frederic Kaplan, and Verena V. Hafner
Venue: IEEE Transactions on Evolutionary Computation (Volume 11, Issue 2)
Year Published: 2007
Keywords: reinforcement learning, evolution, neural networks
Expert Opinion: This paper proposes exploration algorithms based on the idea of intrinsic motivations, in particular motivations to explore in order to maximise the learning progress of a robot. This is a prominent example of the work of the Developmental Robotics community that ties link between developmental psychology, neurosciences and concrete robotics implementation and shows that exploring with this approach to learn to predict action consequences (forward models) results in behavior that is organized and shows similarity with human behavior.