First Max Planck ETH Workshop on Learning Control
11-13 November 2015, Tübingen, Germany
We are pleased to announce the First Max Planck ETH Workshop on Learning Control within the Max Planck ETH Center for Learning Systems. The workshop will take place November 11-13 2015 at the Max Planck Institute for Intelligent Systems (MPI-IS) in Tübingen. 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 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 data-driven approaches for control design, adaptive control, dual control, machine learning for control, online learning, active learning for control, reinforcement learning, and applications of learning control.
The workshop is open to all researchers from MPI-IS and ETH. 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 with ample room for discussions and informal interactions.
We are excited to have the following invited speakers:
Meals (lunch, dinner, coffee breaks) and accommodation for participants from ETH are covered by the Max Planck ETH Center for Learning Systems. However, participants will have to organize their own travels
Accommodation is taken care of by Andrea Odermatt. The following hotels have been booked for ETH participants:
You will receive more information and the hotel you have been accommodated in shortly via email. If you have any questions meanwhile regarding accommodation or other administrative issues, please contact Andrea Odermatt (andrea.odermatt@tuebingen.mpg.de).
Max Planck House | |
Spemannstr. 36 | |
72076 Tübingen | |
Germany | |
+49 (0)7071 601-765 | |
+49 (0)7071 601-790 | |
max-planck-haus@tuebingen.mpg.de |
Due to the construction site, drivers can NOT access the Campus from Spemannstr. anymore! Drivers should use the new central parking lot of the Campus, via "Paul-Ehrlich-Str" - see plan
The walk from the parking lot to the Max Planck House has been shown using a "dashed-green-line".Schedule (talks) & poster sessions
Description | From | To | |
---|---|---|---|
Registration (@Max Planck Haus, lobby) | 16:00 | 17:00 | |
Opening, Invited talk: Melanie Zeilinger: Towards Safe Learning in Control - Leveraging Online Data for Performance
Show details (@Max Planck Haus, lecture hall) |
17:00 | ... | |
Dinner (@Max Planck Haus, conference room) | ... | 21:00 |
Description | From | To | |
---|---|---|---|
Invited talk: Stefan Schaal (@Max Planck Haus, lecture hall) | 09:00 | 10:00 | |
Poster session / coffee - See poster sessions below (@Max Planck Haus, lobby) | 10:00 | 11:30 | |
Participant talks: (@Max Planck Haus, lecture hall) | 11:30 | 12:30 | |
Farbod Farshidian Path Integral Stochastic Optimal Control for Reinforcement Learning Abstract |
11:30 | 11:50 | |
Manuel Wuethrich A New Perspective and Extension of the Gaussian Filter Co-auothors: Sebastian Trimpe, Daniel Kappler and Stefan Schaal Abstract |
11:50 | 12:10 | |
Nicolas Gerig Outcome prediction to assist therapists in selecting exercises in patient-tailored, robot-assisted neurorehabilitation Co-auothors: Georg Rauter, Roland Sigrist, Robert Riener, Peter Wolf Abstract |
12:10 | 12:30 | |
Lunch (@ Max Planck Haus, conference room) | 12:30 | 14:00 | |
Invited talk: Andreas Krause: From Proteins to Robots: Learning to Optimize with Confidence
Show details (@Max Planck Haus, lecture hall) |
14:00 | 15:00 | |
Participant talks (@Max Planck Haus, lecture hall) | 15:00 | 16:20 | |
Alexander Herzog Optimization-based whole-body planning and control under multi-contact interaction Co-auothors: Brahayam Ponton, Stefan Schaal, Ludovic Righetti Abstract |
15:00 | 15:20 | |
Anja Zai Can we infer the microstructure of reinforcement learning from behavioral data? Co-auothors: Alessandro Canopoli, Anna E. Stepien, Richard H.R. Hahnloser Abstract |
15:20 | 15:40 | |
Janis Edelmann Learning Magnetic Control Co-auothors: Andrew Petruska, Ayoung Hong, Samuel Charreyron Abstract |
15:40 | 16:00 | |
Edgar Klenske Dual Control for Approximate Bayesian Reinforcement Learning Co-auothors: Philipp Hennig Abstract |
16:00 | 16:20 | |
Coffee break (@Max Planck Haus, lobby) | 16:20 | 17:00 | |
Panel discussion (@Max Planck Haus, conference room) | 17:00 | 18:00 | |
Conference dinner & focus discussions (@Casino am Neckar, Wöhrdstrasse 25, 72070 Tübingen) | 19:30 | 22:00 |
Description | From | To | |
---|---|---|---|
Invited talk: Bernhard Schölkopf (@Max Planck Haus, lecture hall) | 09:00 | 10:00 | |
Poster session / coffee - See poster sessions below (@Max Planck Haus, lobby) | 10:00 | 11:30 | |
Invited talk: Pieter Abbeel: Making Robots Learn - Show details (@Max Planck Haus, lecture hall) | 11:30 | 12:30 | |
Lunch (@Max Planck Haus, conference room) | 12:30 | 14:00 | |
Participant talks (@Max Planck Haus, lecture hall) | 14:00 | 15:00 | |
Felix Berkenkamp Learning-based Robust Control: Guaranteeing Stability while Improving Performance Co-auothors: Angela P. Schoellig Abstract |
14:00 | 14:20 | |
Alonso Marco Automatic LQR Tuning Based on Gaussian Process Optimization Co-auothors: Philipp Hennig, Jeannette Bohg, Stefan Schaal and Sebastian Trimpe Abstract |
14:20 | 14:40 | |
Tobias Sutter Decision making under uncertainty: Performance bounds for the scenario approach Co-auothors: Peyman Mohajerin Esfahani, John Lygeros Abstract |
14:40 | 15:00 | |
Closing remarks (@Max Planck Haus, lecture hall) | 15:00 | 15:15 | |
Lab tours (meeting: @Max Planck Haus, lobby) | 15:30 | 17:00 | |
MPI Friday beer (@Spemannstr. 41, PS dept.) | 17:00 | ... |
November 12th (Thursday) |
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Author | Title | Co-authors | |
---|---|---|---|
Daniel Kappler | Data-Driven Online Decision Making for Autonomous Manipulation | Peter Pastor, Manuel Wuethrich, Jeannette Bohg, Stefan Schaal | Abstract |
Chengzhi Hu | Real Time Control and Monitoring of Plant Cell Micro-Indention via Cellular Force Microscope | Jan Burri | Abstract |
Jim Mainprice | Using Inverse Optimal Control To Learn Collaborative Human Reaching Motion Policies | Rafi Hayne, Dmitry Berenson | Abstract |
Andreas Doerr | Adaptive and Learning Concepts in Hydraulic Force Control | Cédric de Crousaz, Ludovic Righetti, Sebastian Trimpe | Abstract |
Fabian Just | Enhancing robotic arm rehabilitation through intelligent interaction between the patient, the therapist, and the rehabilitation robot | Robert Riener, Georg Rauter | Abstract |
Robin Oswald | Velocity Control of Trapped Ions for Transport Quantum Logic Gates | Abstract | |
Burak Zeydan | Reinforcement learning for particle manipulation with the RodBot | Roel Pieters, Bradley J. Nelson | Abstract |
Dieter Büchler | Using Pneumatic Artificial Muscles to Facilitate Robot Learning Performance | Yanlong Huang, Jan Peters | Abstract |
Stefano Palagi | Towards bioinspired self-adaptive soft microrobots | Peer Fischer | Abstract |
Michael Neunert | Integrating Optimal Control and Learning | Farbod Farshidian, Jonas Buchli | Abstract |
Tobias Sutter | Asymptotic Capacity of a Random Channel | David Sutter, John Lygeros | Abstract |
Nitish Kumar | Agile Digital Fabrication: Robotics for manufacturing at the large scale | Timothy Sandy, Markus Giftthaler |
Abstract
Abstract Abstract |
November 13th (Friday) |
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Author | Title | Co-authors | |
Simon Ebner | Adaptive Communication for Control | Sebastian Trimpe | Abstract |
Johannes Pfleging | Learning tool use to infer prehistoric human behaviour | Jonas Buchli | Abstract |
Miroslav Bogdanovic | Imitation learning for games with convolutional networks | Abstract | |
Jemin Hwangbo | Foothold Selection Using Direct State-to-Action Mapping | Marco Hutter | Abstract |
Thiago Boaventura | Learning transparency controllers for exoskeleton robots | Jonas Buchli | Abstract |
Mazen Al Borno | Domain of Attraction Expansion for Physics-Based Characters | Javier Romero | Abstract |
Okan Koc | Cautious Learning Control with Total Least Squares | Guilherme Maeda, Jan Peters | Abstract |
Franziska Meier | Drifting Gaussian Processes for Online Model Learning | Stefan Schaal | Abstract |
Jakob Buhmann | Communication in a distributed and hierarchical control system | Matthew Cook | Abstract |
Alexander Winkler | Tracking optimized and learned whole body motions on real robots | Jonas Buchli | Abstract |
Amin Rezaeizadeh | Iterative Learning Control Application in the SwissFEL | Roy S. Smith | Abstract |
Diego Pardo | Learning Rigid Body Dynamics of Constrained Multibody Systems | Jonas Buchli | Abstract |
For questions regarding travel, accommodation and administrative matters, please contact Andrea Odermatt: