AC4: Developmental Robotics
This course will give an introduction to developmental robotics and computational models used for sensorimotor learning in robots. In the sessions, we will cover sensorimotor learning, predictive models, joint attention and the development of an artificial self.Objectives
The objectives of this course are to understand how developmental processes can be implemented and tested in artificial systems that interact with themselves, others and the environment.
Schillaci, G., Hafner, V.V., Lara, B. (Editors) (2016). Re-enacting sensorimotor experience for cognition, Research Topic in Frontiers in Robotics and AI, Section Humanoid Robotics. doi: 10.3389/ frobt.2016.00077
Schillaci, G., Hafner, V.V., Lara, B. (2016), Exploration behaviours, body representations and simulation processes for the development of cognition in artificial agents, Frontiers in Robotics and AI, section Humanoid Robotics, 3:39. doi: 10.3389/frobt.2016.00039
Schillaci, G., Ritter, C.-N., Hafner, V.V., Lara, B. (2016), Body Representations for Robot Ego-Noise Modelling and Prediction. Towards the Development of a Sense of Agency in Artificial Agents, International Conference on the Simulation and Synthesis of Living Systems (ALife XV), pp. 390-397, Mexico, July 2016
Cangelosi, A. and Schlesinger, M. (2015), Developmental Robotics - From Babies to Robots, MIT Press.
Verena Hafner is Professor of Adaptive Systems at the Department of Computer Science at Humboldt-Universität zu Berlin. She holds a Master with distinction in Computer Science and AI from the University of Sussex, UK, and a PhD from the Artificial Intelligence Lab, University of Zurich, Switzerland. Before moving to Berlin, she worked as an associate researcher in the Developmental Robotics Group at Sony Computer Science Labs in Paris, France. She is part of the Programme Committee of the DFG Priority Programme The Active Self (SPP 2134), PI in the graduate school on sensory computation in neural systems (DFG, 2010-2019) and PI in the EU FP7 project EARS on Embodied Audition for RobotS (2014-2017). Her research interests include sensorimotor interaction and learning, joint attention, internal models, behaviour recognition, and the artificial self.