RSS-CLeaR-2019: RSS Workshop: Combining Learning and Reasoning - Towards Human-Level Robot Intelligence Freiburg, Germany, June 22, 2019 |
Conference website | https://sites.google.com/view/rss19-learning-and-reasoning |
Submission link | https://easychair.org/conferences/?conf=rssclear2019 |
Submission deadline | June 5, 2019 |
Dear colleagues,
we are excited to announce a full-day workshop on “Combining Learning and Reasoning - Towards Human-Level Robot Intelligence” at RSS 2019.
Robotics research has developed powerful model-based methods for perception, state estimation, planning, control, etc., which form the building blocks of the vast majority of successful robot systems. At the same time, data-driven, model-free learning has recently brought unprecedented success in various domains, where model-based methods struggle despite decades of research. The aim of this workshop is to bring together researchers from robotics and machine learning, and discuss opportunities and challenges towards building human-level robot intelligence, in particular, combining model-based reasoning and data-driven learning in a scalable and composable manner.
Some questions we would like to discuss:
-
What is the role of model-based reasoning and model-free learning in an intelligent robot system?
-
Can we learn intelligent robot behaviour only from reinforcements? Is expert knowledge essential?
-
How do we combine existing knowledge with data-driven learning? What should be built in and what should be learned?
-
How do we integrate solutions for small, isolated sub-tasks into a large intelligent system? How do we combine model-based and model-free components? Would we build Shakey differently today?
-
Is robot intelligence going to be explainable? Is interpretability unnecessary, good to have, or a must?
Invited Speakers
-
Sidd Srinivasa, University of Washington
-
Raia Hadsell, Google DeepMind
-
Alberto Rodriguez, Massachusetts Institute of Technology
-
David Hsu, National University of Singapore
-
Dieter Fox, University of Washington (tentative)
-
Theophane Weber, Google DeepMind (tentative)
Submission:
We invite participants from all fields of robotics to submit extended abstracts related to the workshop topic, anywhere on the spectrum between model-free learning and model-based reasoning. Submissions should be up to 2-4 pages + references in RSS format.
Accepted submissions will be presented in 2-minute spotlight talks and in a dedicated poster session. Selected contributions may receive a longer presentation slot.
Important Dates:
-
Submission deadline: May 31 (AOE)
-
Notification of acceptance: June 8
-
Camera-ready deadline: June 21
-
Workshop: June 22
Organizers:
-
Peter Karkus, National University of Singapore
-
Alina Kloss, Max Planck Institute for Intelligent Systems
-
Rico Jonschkowski, Robotics at Google
-
Leslie P. Kaelbling, Massachusetts Institute of Technology
Contact: karkus@comp.nus.edu.sg (general), alina.kloss@tuebingen.mpg.de (submissions