Our aim is to give robots the ability to develop autonomously new skills. In particular, we focus on learning to control a robotic body in a developmental fashion. Artificial intrinsic motivations are a central component that we develop using information theory and dynamical systems theory. We work on reinforcement learning, representation learning, and internal model learning.
For further details visit the
Website: georg.playfulmachines.com.
Google scholar: scholar.google.de/citations?user=b-JF-UIAAAAJ
In this project, we develop specific machine learning methods for identifying an underlying functional form that gave rise to data. In particular for mechanical systems which are governed by the laws of physics, if we can learn the actual equations then accurate predictions outside of the domain of the available dat... Read More
Research conducted by members of the group prior to joining the Max-Planck-Institute for Intelligent Systems is presented in this category. Read More
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