The International Workshop on Intelligent Autonomous Learning Systems is a yearly by-invitation-only workshop on developments within machine learning for robotics and other autonomous systems. The focus lies on fundamental scientific and organizational discussions. The workshop typically takes place in Kleinwalsertal (Austria), a nice location surrounded by the beautiful Alps.
International Workshop of Intelligent Autonomous Learning Systems 2022
Quick Facts
Organizers: | Joao Carvalho, Pascal Klink, Joe Watson |
Location: | Darmstädter Haus, Kleinwalsertal, Austria |
Dates: | 14.08.- 21.08.2022 |
Schedule
Note, the schedule is subject to change, to optimize the weather during outdoor activites.
Daily Schedule
14/8 | Sunday: | Travel. |
---|---|---|
15/8 | Monday: | Introductions, Tutorial #1, Networking |
16/8 | Tuesday: | Talk #1, Tutorial #2 |
17/8 | Wednesday: | Talk #2, Group Discussions |
18/8 | Thursday: | Hike, Tutorial #3 |
19/8 | Friday: | Group discussions, Hackathon |
20/8 | Saturday: | Discussions / Swimming pool, Sauna |
21/8 | Sunday: | Travel back |
Detailed Schedule
Note, there will be 30 minute coffee breaks each morning and afternoon, between sessions.
Time | Monday | Tuesday | Wednesday | Thursday | Friday |
---|---|---|---|---|---|
09 - 10 | Introduction | Hike | Open-source Reinforcement Learning | A Robotic Platform for Air Hockey | Geri Neumann (ALR, KIT) |
10 - 11 | Network Speed Dating | Hike | Information-Theoretic Sensorimotor Behaviour I | Information-Theoretic Sensorimotor Behaviour II | Latent Predictive World Models |
11 - 12 | WIAWIWTB | Hike | Information-Theoretic Sensorimotor Behaviour I | Information-Theoretic Sensorimotor Behaviour II | Latent Predictive World Models |
12 - 13 | Lunch | Hike | Lunch | Lunch | Lunch |
13 - 14 | WIAWIWTB | Hike | (IAS) Ops, DevOps & IT Discussion | ML for Drug Discovery | Joni Pajarinen (Aalto) |
14 - 15 | WIAWIWTB | Hike | (IAS) Feedback Discussion | Research Speed Dating | Impactful Research Workshop |
15 - 16 | WIAWIWTB | Hike | (IAS) Teaching Review | (IAS) Research Review | |
16 - 17 | Hike | (IAS) 360° Feedback | (IAS) Research Review |
Invited Tutorials
Information-Theoretic Treatment of the Perception-Action Loop
Daniel Polani is a professor of Artificial Intelligence and Director of the Centre for Computer Science and Informatics Research (CCSIR), and Head of the Adaptive Systems Research Group, and leader of the SEPIA (Sensor Evolution, Processing, Information and Actuation) Lab at the University of Hertfordshire. Daniel Polani received the Doctor of Natural Sciences degree from the Faculty of Mathematics and Computer Science, University of Mainz, Mainz, Germany, in 1996.,From 1996 to 2000, he was a Research Assistant with the Faculty of Mathematics and Computer Science, University of Mainz. In 1997, he was a Visiting Researcher with the Neural Networks Research Group, University of Texas at Austin, Austin, TX, USA. From 2000 to 2002, he was a Research Fellow with the Institute for Neuro- and Bioinformatics, University of Lübeck, Lübeck, Germany. From 2002 to 2008, he was a Principal Lecturer with the Adaptive Systems and Algorithms Research Groups, School of Computer Science, University of Hertfordshire (UH), Hatfield, U.K. Since 2008, he has been a Reader in Artificial Life and Member of the Adaptive Systems and Algorithms Research Groups, School of Computer Science, UH. His research interests include the foundations of intelligent behavior in biological as well as artificial agents, especially in terms of informational optimality principles.
A Unified Framework for Developing Curiosity-driven Agents in Hard-Exploration Tasks using Latent-Predictive World-models. (Remote)
Mohammad Gheshlaghi Azar is a research scientist at DeepMind woking on broad range of topics from deep reinforcement learning to self-supervised learning. His main passion is to gain better understanding of the concept of intelligence by looking deeper on its governing mathematical principles.
Contributed Talks
Machine Learning for Drug Discovery
Alexander I. Cowen-Rivers is a PhD student in the Intelligent Autonomous Systems group and Research Scientist at Huawei Research London, working on Reinforcement Learning and Bayesian Optimisation. Alexander joined the lab in November 2019 after receiving his MSc in Machine Learning & Data Science from University College London in October 2018.
A Robotic Platform for Air Hockey
Puze Liu is a PhD student in the Intelligent Autonomous Systems group. His research interests include robotics, reinforcement learning, inverse reinforcement learning, and human-robot collaboration. Puze is looking for new approaches for robots to learn collaborative tasks that enable robots assisting humans in different scenarios.
Open-source Reinforcement Learning
Davide Tateo is a postdoctoral researcher in the Intelligent Autonomous Systems group working on Robotics and Reinforcement Learning.
Workshop Activities
WIAWIWTB (Where I Am & Where I Want To Be)
A series of brief 3 minute lightning talks summarizing your research career so far and future aspirations for all retreat participlants. Talks are up to three minutes long, with two minutes allocated per speaker for discussion. Chair: Joe Watson
Impactful Research Workshop
What makes impactful research? How should we choose problems to work on? This workshop aims to develop strategies for finding the good research questions and classifying dead ends, and discuss the current open questions in Robot Learning. Chair: Joe Watson
Network and Research Speed Dating
Rapid three minutes chats to get to know each other, and establish potential research collaborations. Open to all. Chair: Joe Watson
IAS Workshops
IAS-only meetings to discuss various internal matters. Other participants are free to have their own meetings or use these slots freely. Chairs: Joe Watson and Joao Carvalho
Tooling Tutorials
Contributed workshops looking at a specific problems or software libraries. Chairs: Boris Belousov (Isaac Gym), Daniel Palenicek (JAX) and Joe Watson (RevealJS)
Travel Arrangements
Please contact Pascal Klink for travel advice.