Sebastian Höfer

Lachine Mearning. Borotics. Irtificial Antelligence.

About Me

Applied Scientist at Amazon Core Machine Learning Berlin
PhD in Computer Science (Robotics / Machine Learning)

Before starting my position at Amazon, I graduated from the Robotics & Biology Lab, TU Berlin. My research activities span a variety of topics in the area of artificial intelligence, ranging from robotics, computer vision and artificial language evolution to reinforcement, unsupervised and semi-supervised learning. Before my time in academia, I co-founded and worked for several internet start-ups in Berlin.

News

14/10/2017: Our paper on Opening a Lockbox through Physical Exploration got accepted at Humanoids!

20/08/2017: I'm officially a PhD now! You find my thesis On Decomposability in Robot Reinforcement Learning online.

Projects

An excerpt of the projects that I completed in the last years.

PhD thesis: On Decomposability in Robot Reinforcement Learning

In my thesis, I studied two problems in robot learning, ball catching and learning manipulate articulated object, and I developed a conceptual framework for understanding solutions to these problems: the spectrum of decomposability.

Blog on Intuitive Machine Intelligence

My blog on teaching machine learning and artificial intelligence without formal math.

CAPEL

Research paper on coupled learning of relational forward models and action parameters, presented at IROS 2016.

Contact

Email me at mail - at - firstnamelastname - dot - de.

Publications

Manuel Baum*, Matthew Bernstein*, Roberto Martín-Martín*, Sebastian Höfer, Johannes Kulick, Marc Toussaint, Alex Kacelnik, Oliver Brock. Opening a Lockbox through Physical Exploration. Humanoids, Birmingham, UK, November 2017.

Sebastian Höfer. On decomposability in robot reinforcement learning. Dissertation. Technische Universität Berlin, Germany, June 2017.

Antonin Raffin*, Sebastian Höfer*, Rico Jonschkowski, Oliver Brock, and Freek Stulp. Unsupervised Learning of State Representations for Multiple Tasks. NIPS Workshop on Deep Learning for Action and Interaction, Barcelona, Spain, December 2016.

Sebastian Höfer and Oliver Brock. Coupled Learning of Action Parameters and Forward Models for Manipulation. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016.

Rico Jonschkowski and Clemens Eppner* and Sebastian Höfer* and Roberto Martín-Martín* and Oliver Brock. Probabilistic Multi-Class Segmentation for the Amazon Picking Challenge. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016.

Clemens Eppner* and Sebastian Höfer* and Rico Jonschkowski* and Roberto Martín-Martín* and Arne Sieverling* and Vincent Wall* and Oliver Brock. Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems. Proceedings of Robotics: Science and Systems, 2016.

Roberto Martín-Martín and Sebastian Höfer and Oliver Brock. An Integrated Approach to Visual Perception of Articulated Objects. Proceedings of the IEEE International Conference on Robotics and Automation, pp. 5091 - 5097, 2016.

Rico Jonschkowski* and Sebastian Höfer* and Oliver Brock. Patterns for Learning with Side Information. arXiv:1511.06429 [cs.LG] : 2016.

Marcus Buckmann and Robert Gaschler and Sebastian Höfer and Dennis Loeben and Peter A. Frensch and Oliver Brock. Learning to Explore the Structure of Kinematic Objects in a Virtual Environment. Frontiers in Psychology 6(374): 2015.

Malte Lorbach and Sebastian Höfer and Oliver Brock. Prior-Assisted Propagation of Spatial Information for Object Search. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2904-2909, 2014.

Sebastian Höfer and Tobias Lang and Oliver Brock. Extracting Kinematic Background Knowledge from Interactions Using Task-Sensitive Relational Learning. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 4342-4347, 2014.

Sebastian Höfer and Oliver Brock. Learning Compact Relational Models for the Exploration of Articulated Objects. Proceedings of the ICRA Mobile Manipulation Workshop on Interactive Perception (ICRA), 2013.

Luc Steels and Michael Spranger and Remi van Trijp and Sebastian Höfer and Manfred Hild. Emergent Action Language on Real Robots. Language Grounding in Robots. Springer (US), chap. 13, 255-276, 2012.

Katrien Beuls and Luc Steels and Sebastian Höfer. The Emergence of Internal Agreement Systems. Experiments in Cultural Language Evolution, pp. 233-256, 2012.

Sebastian Höfer and Michael Spranger and Manfred Hild. Posture Recognition Based on Slow Feature Analysis. Language Grounding in Robots. Springer Verlag, chap. 06, 111-130, 2012.

Katrien Beuls and Sebastian Höfer. Simulating the Emergence of Grammatical Agreement in Multi-agent Language Games. Twenty-Second International Joint Conference on Artificial Intelligence, pp. 61-66, 2011.

Sebastian Höfer. Anwendungen der Slow Feature Analysis in der humanoiden Robotik. Diploma Thesis, Humboldt University of Berlin, Germany, 2011.

Sebastian Höfer and Manfred Hild and Matthias Kubisch. Using Slow Feature Analysis to Extract Behavioural Manifolds Related to Humanoid Robot Postures. Tenth International Conference on Epigenetic Robotics, pp. 43-50, 2010.

Sebastian Höfer and Manfred Hild. Using Slow Feature Analysis to Improve the Reactivity of a Humanoid Robot's Sensorimotor Gait Pattern. International Conference on Neural Computation, pp. 212-219, 2010.

Michael Spranger and Sebastian Höfer and Manfred Hild. Biologically Inspired Posture Recognition and Posture Change Detection for Humanoid Robots. IEEE International Conference on Robotics and Biomimetics, pp. 562-567, 2009.

* = shared first authorship.