Second Max Planck ETH Workshop on Learning Control
8/9 Febuary 2018, Zurich, Switzerland
After a successful first edition in 2015, we are pleased to announce the second workshop on Learning Control within the Max Planck ETH Center for Learning Systems. The workshop will take place February 8-9 2018 at ETH Zurich. We cordially invite all researchers from ETH Zürich and MPI-IS interested in the area of Learning Control to participate and actively contribute to this workshop.
The workshop aims at bringing together researchers from ETH Zürich and MPI-IS working in the area of Learning Control in order to create and grow a community of interest within the Max Planck ETH Center for Learning Systems. The workshop will provide a platform to exchange ideas, present current research, discuss challenges for Learning Control, and initiate future research collaborations within the Center.
The topic and scope of this workshop is Learning Control. Albeit not uniquely defined, we understand Learning Control as the rather broad research area that lies at the intersection of Machine Learning and Automatic Control. This includes, but is not limited to reinforcement learning, machine learning for control, data-driven control, adaptive control, dual control, online learning, active learning for control, model learning, and applications of learning control.
The workshop is open to all researchers from MPI-IS and ETH. Nevertheless, applications of external researchers are possible, though priority will be given to researchers from MPI-IS and ETH (depending on available places). We seek to create an informal atmosphere to foster open discussions and exchange of ideas.
All participants are asked to submit a maximum one page abstract detailing their research interests. In addition to presenting research results in the area of Learning Control, we encourage participants to also include open research questions, early ideas, or any topic that can lead to interesting and fruitful discussions in this exciting area.
Submissions will be briefly reviewed to ensure adequacy with the scope of the workshop. A few submissions will be selected for short plenary presentation. All other accepted submissions will be presented in interactive poster format.
In addition to interactive presentations and short talks, there will be invited keynote talks, a panel discussion, as well as social events (dinner on Thursday evening) with ample room for discussions and informal interactions.
We are excited to have the following invited speakers:
Accommodation and travel costs for participants from MPI-IS (CLS members, associated members, students / co-workers of their groups) are covered by the Max Planck ETH Center for Learning Systems.
The following hotels have been booked.
Meals (lunch, dinner, coffee breaks) are offered for all participants.
ETH Zurich | |
Department of Computer Science | |
CAB Building | |
Universitätsstrasse 6 | |
8092 Zurich |
Directions from Zurich main station to CAB building:
Tram no. 6 (direction Zoo) or Tram no. 10 (direction Airport) to stop „ETH/UniversitätsSpital“.
The dinner on Thursday evening Feb 8, 2018 will be at Hotel Uto Kulm on top of Uetliberg (detailed information will be provided during the workshop).
Directions to Uetliberg (dinner):
From ETH/Universitätspital to Zurich Main station take Tram 6 Direction Enge or Tram 10 Direction Bahnhofplatz. From Zurich main station, take the Sihltal Zurich-Uetliberg Bahn SZU (S10) from the underground station on track 21/22. The SZU runs weekdays every half-hour and takes 20 min to get to Uetliberg station. From there it is a 7 minute walk to the hotel.
Trams 6/10 from ETH/Universitätsspital need 6-7 minutes to Zurich main station and run every 5-10 minutes. The train schedule from Zurich main station is as follows:
Schedule (talks) & poster sessions
Description | From | To | |
---|---|---|---|
train from TUe to ZH HB: arrive 10:25/11:25/12:25 | |||
Registration | 11:00 | 13:00 | |
Lunch (Standing lunch in the Foyer CAB G 10.005) | 12:00 | 13:00 | |
Opening | 13:00 | 13:15 | |
Invited talk: Thomas Schön: System identification meets the Gaussian process (50 min + Q/A)
Show details |
13:15 | 14:15 | |
Poster session / coffee - See poster sessions below | 14:15 | 16:00 | |
Participant talks: | 16:00 | 17:00 | |
Matteo Turchetta Goal Oriented Safe Exploration in Discrete Markov Decision Processes Co-Authors: Felix Berkenkamp, Andreas Krause Abstract |
16:00 | 16:15 | |
Andreas Doerr Robust Learning of dynamics models for model-based policy search Co-Authors: Christian Daniel, Duy Nguyen-Tuong, Alonso Marco, Stefan Schaal, Marc Toussaint, Sebastian Trimpe Abstract |
16:20 | 16:35 | |
Ruben Grandia Model learning for legged robots Co-Authors: Marco Hutter Abstract |
16:40 | 16:55 | |
Travel Uetliberg (Meeting point: CAB Building Registration area) | 17:30 | 18:30 | |
Dinner (Hotel Utokulm, Uetliberg) | 19:00 | 23:00 |
Description | From | To | |
---|---|---|---|
Invited talk: Nicolas Heess: Deep reinforcement learning for control -- algorithms and architectures Show details |
09:00 | 10:00 | |
Poster session / coffee - See poster sessions below | 10:00 | 11:50 | |
Participant talks: | 11:50 | 12:30 | |
Arash Mehrjou Controlled Generative Adversarial Networks Co-Authors: Bernhard Schölkopf, Saeed Saremi Abstract |
11:50 | 12:05 | |
Sebastian Blaes Using Embodied Exploration for Reinforcement Learning Co-Authors: Jia-Jie Zhu, Georg Martius Abstract |
12:10 | 12:25 | |
Lunch (Standing lunch in the Foyer CAB G 10.005) | 12:30 | 14:00 | |
Invited talk: John Lygeros:A statistical learning perspective on scenario optimisation (50 min + Q/A)
Show details |
14:00 | 15:00 | |
Participant talks: | 15:00 | 16:00 | |
Daniel Kappler Increasing Sample-Efficiency via Online Meta-Learning Co-Authors: Stefan Schaal and Franziska Meier Abstract |
15:00 | 15:15 | |
Kim Peter Wabersich Model predictive safety certificates from data for learning-based control Co-Authors: Melanie N. Zeilinger Abstract |
15:20 | 15:35 | |
Carmelo Sferrazza Iterative learning for the generation and tracking of trajectories using parametrized model predictive control Co-Authors: Michael Muehlebach, Raffaello D’Andrea Abstract |
15:40 | 15:55 | |
Closing | 16:00 | 16:15 |
Febuary 8th (Thursday) |
|||
Author | Title | Co-authors | |
---|---|---|---|
Carl Jidling | Linearly constrained Gaussian processes | Niklas Wahlström, Adrian Wills, Thomas B. Schön | Abstract |
Sebastian Curi | Ph. D. Research goals Robust reinforcement learning | Abstract | |
Dominik Baumann | Learning to Save Communication | Friedrich Solowjow, Sebastian Trimpe | Abstract |
Aravind Elanjimattathil Vijayan | Approaches to solving simultaneous control and locomotion problem for quadrupeds with manipulators | Abstract | |
Markus Giftthaler | The ‘Control Toolbox’ - An Open-Source C++ Library for Robot Modelling, Control, Estimation and Learning | Michael Neunert, Jonas Buchli | Abstract |
Ashish Cherukuri | Data-driven distributed optimization for multiagent systems | Abstract | |
Oleksandr Zlatov | Implementation and investigation of some state-of-the-art deep reinforcement learning approaches | Sebastian Trimpe | Abstract |
David Hoeller | Reinforcement Learning in Simulation | (doing PhD with Marco Hutter, remark by MS) | Abstract |
Samuel Bustamante | Continuous control of a robotic arm with a non-invasive brain-machine interface | Moritz Grosse-Wentrup | Abstract |
Jan Carius | Nonlinear Optimal Control for Switched Systems | Farbod Farshidian | Abstract |
Alexander von Rohr | Learning Control for Adaptive Locomotion of Soft Microrobots | Stefano Palagi, Sebastian Trimpe | Abstract |
Mohammad Khosravi | Learning the Energy Consumption in Buildings: A Joint Classification and Nonlinear Regression Algorithm | Annika Eichler, Roy Smith | Abstract |
Stefan Stevsic | Learning Robot Control from End-user Specifications | Manuel Kaufmann | Abstract |
Jia-Jie Zhu | Guiding Meta Reinforcement Learning using Optimal Control | Georg Martius, MPI-IS | Abstract |
Julian Zilly | A spectral learning theory for robotics | Andrea Censi, Jacopo Tani, Emilio Frazzoli | Abstract |
Lukas Hewing | Cautious Nonlinear Model Predictive Control with Gaussian Process Dynamics | Melanie N. Zeilinger | Abstract |
Angeliki Kamoutsi | Data-driven approximate dynamic programming: A linear programming approach | Tobias Sutter, Angeliki Kamoutsi, Peyman Mohajerin Esfahani, and John Lygeros | Abstract |
Matthias Hofer | Learning Control for Soft Robotic Manipulator | Abstract | |
Elena Arcari | Uncertainty Learning and Control of a Robotic Arm | Elena Arcari, Andrea Carron, Lukas Hewing, Markus Giftthaler, Melanie N. Zeilinger | Abstract |
Luca Perrozzi | Deep learning for jet reconstruction in the CMS experiment | Elena Arcari, Andrea Carron, Lukas Hewing, Markus Giftthaler, Melanie N. Zeilinger | Abstract |
Febuary 9th (Friday) |
|||
Author | Title | Co-authors | |
Steve Heim | Designing Natural Dynamics that are Easy to Exploit | Abstract | |
Danny Driess | Learning to Control Redundant Musculoskeletal Systems | Daniel Hennes, Marc Toussaint, Syn Schmitt | Abstract |
Konstantinos Kokkalis | Locally Weighted Learning Control with Stability Guarantees | Konstantinos Kokkalis, Sebastian Trimpe | Abstract |
Okan Koc | Optimizing Robot Striking Movements with Iterative Learning Control | Guilherme Maeda, Jan Peters | Abstract |
Vinay Jayaram | Reinforcement learning for prosthetic control | Abstract | |
Vassilios Tsounis | Hierarchical Reinforcement Learning for Hybrid Control in Legged Locomotion | Abstract | |
Dengxin Dai | PathTrack: Fast Trajectory Annotation with Path Supervision | Santiago Manen, Michael Gygli, Dengxin Dai, Luc Van Gool | Abstract |
Xiaoguang Dong | Planning Spin-Walking Locomotion for Automatic Grasping of Microobjects by An Untethered Magnetic Microgripper | Metin Sitti | Abstract |
Zahra Grosser | Vibration Detection and Suppression for Distributed Mechanical Systems | Melanie N Zeilinger | Abstract |
Andrea Carron | Safe Learning for Distributed Systems | Abstract | |
Marcel Menner | Personalizing Human-in-the-Loop Control Systems | Melanie Zeilinger | Abstract |
Michal Rolínek | Extrapolation via Learning Physics | G. Martius, F. Solowjow, S. Trimpe | Abstract |
Johannes Kirschner | Stochastic Bandits with Heteroscedastic Noise | Andreas Krause | Abstract |
Cristina Pinneri | Self-organized discovery of goal-free behaviors: a new way to interactive robotics | Georg Martius | Abstract |
Edgar Klenske | The Spectrum of Dual Control | Abstract | |
Angeliki Kamoutsi | A scenario based approach to data-driven inverse stochastic optimal control | Angeliki kamoutsi, Tobias Sutter, John Lygeros | Abstract |
Manuel Wuthrich | Approximation Maximization - a Novel Policy Optimization Algorithm | Alexander Herzog, Stefan Schaal | Abstract |
Alonso Marco | On the Design of LQR Kernels for Efficient Controller Learning | Philipp Hennig, Stefan Schaal, and Sebastian Trimpe | Abstract |
Lukas Fröhlich | Active Model Learning for Feedback Controlled Dynamic Systems | Edgar Klenske, Melanie N. Zeilinger | Abstract |
Event registration is now closed