Learning and Adaptation for Sensorimotor Control: Workshop Program

08:45	Introduction
09:00	Learning in the field how to soar like a bird Terrence Sejnowski, Salk Institute and University of California at San Diego Safe model-based learning for robot control Felix Berkenkamp, ETH Zürich, Switzerland
10:20	Coffee
10:40	Measuring motion complexity and its applications to learning of motion skills. Il-Hong Suh, Hanyang University, Korea Accumulation of evidence to a decision boundary in an active sensorimotor behavior Mathew Diamond, International School for Advanced Studies, Italy
12:00	Lunch
14:00	Positive feedback regulation Rodolphe Sepulchre, University of Cambridge, UK Universal laws and architectures in complex networked systems John Doyle, Caltech, USA
15:20	Coffee
15:40	How to make artificial agents a bit more like us Hedvig Kjellström, KTH Royal Institute of Technology, Sweden. Sensorimotor control as the result of the synergistic coupling of feedback and feedforward control through counterfactual errors Paul Verschure, Universitat Pompeu Fabra, Barcelona
17:00	End of day

09:00	The post-natal development of hippocampal networks for memory and space Thomas Wills, UCL, UK It takes two to tango: Cerebellar modules and learning rules Chris de Zeeuw, Netherlands Institute for Neuroscience, Amsterdam
10:20	Coffee
10:40	We Don't Need No Annotation: Efficient Training for Image Retrieval Ondrej Chum, Czech Technical University, Prague Efficient AI: Probabilistic machine learning and control Patrick van der Smagt, Technical University of Munich and Volkswagen Group, Germany
12:00	Lunch
14:00	Control of food intake, appetite and satiety Marie Csete, Caltech, USA Investigating animal locomotion using mathematical models and biorobots Auke Ijspert, Biorobotics Laboratory, EPFL,Lausanne
15:20	Coffee
15:40	Learning to control the linear quadratic regulator Ben Recht, UC Berkeley
16:20	Discussion
17:00	End of lectures
	Workshop Dinner at Hypoteket (Kyrkogatan 13) 19h00

09:00	Adaptive Control — A Perspective Karl Johan Åström, Automatic Control, Lund University Assembling stochastic quasi-Newton algorithms using Gaussian processes Thomas Schön, Uppsala University, Sweden
10:20	Coffee
10:40	Some outstanding challenges in reinforcement learning Csaba Szepesvari, University of Alberta, Canada Collective computation and learning in nonlinear networks Jean-Jacques Slotine, MIT
12:00	Lunch
14:00	Brain circuitry analysis of self-organizing interfaces between the brain and the external world Henrik Jörntell, Neural Basis of Sensorimotor Control, Lund University Action-based learning in sensorimotor systems Per Petersson, Integrative Neurophysiology, Lund University
15:20	Coffee
	End of workshop

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