Kevin Sebastian Luck

Assistant Professor

I am an Assistant Professor in the Computatioal Intelligence Group at the Vrije Universiteit Amsterdam. Here, I am working on multiple different topics in the field of robot learning, primarily in the area of deep reinforcement learning.

One area of particular interest of mine is the combination of deep reinforcement learning with evolutionary principles, for the development of AI-assisted design methodologies and physical/embodied intelligence, to allow robots to co-adapt both their behaviour and morpoholgy.

Before I joined Amsterdam I worked as postdoctoral researcher at the Aalto University and the Finnish Center for Artificial Intelligence in Espoo (Helsinki), Finland, where I am/was hosted by the Intelligent Robotics Group of Ville Kyrki.

Keywords: (Deep) Reinforcement Learning, Robot Learning, Embodied Intelligence, Evolving Robots

news

Sep 23, 2024	We presented our abstract about applying co-design to snake robots at the 40th ICRA anniversity conference (ICRA@40) in Rotterdam, Netherlands. This was work done by my two amazing Master students Riccardo Pretto and Sylvia Cressman, in collaboration with Michael Andrew Jansen from the Smithsonian Institute in Washington DC, and my two finnish collegues Shivam Chaubey and Ville Kyrki.
Sep 16, 2024	Happy to welcome Mohammadreza Nakhaei as a visiting PhD student to my group for the next 5 months.
Sep 01, 2024	Bringing more Robotics to the VU Amsterdam! Starting now in the new academic year we will have for the first time a foundational Robotics course in the CS/AI curriculum for Bachelor students. Lot’s of work, but we have assembled a great team with Kim Baraka as co-teacher and Mark Adamik as the lead for the practicals.
Aug 30, 2024	I presented our work on Accelerating Laboratory Automation Through Robot Skill Learning For Sample Scraping at IEEE CASE 2024 in Bari, Italy. This was a collaboration with an amazing team at the University of Liverpool, shout-out to my awesome collegue Gabriella Pizzuto for putting this work together! The paper was also nominated for the Best Healthcare Application award at CASE 2024!
Jul 25, 2024	I gave an invited talk about our research on Co-Design with Robot Learning at the MILA Robot Learning Seminar.
Jul 15, 2024	Congratulations to Sergio Hernandez! Our paper Following Ancestral Footsteps: Co-Designing Agent Morphology and Behaviour with Self-Imitation Learning won the best paper award at the R:SS Workshop on Embodiment-Aware Robot Learning (EARL).
Jul 15, 2024	I gave an invited talk at the R:SS Workshop on Embodiment-Aware Robot Learning (EARL) with the title “Co-Adaptation of Robot Design & Behavior: A Reinforcement Learning Perspective”.
Jul 10, 2024	We are hiring: We are looking for a postdoctoral researcher interested to work on Large Language Models, Representation Learning and Robot Learning. In the context of the NWO funded project TeNet we have a short-term postdoctoral position at the Vrije Universiteit Amsterdam for a maximum of 1 year, with the possibility of a research visit at the Finnish Center for AI and Aalto University in Helsinki, Finland, including a secondment to FCAI for 2-3 months. If this sounds interesting to you, consider applying here.
Jun 04, 2024	Our work on automated chemical experiments with robots powered by reinforcement learning got accepted to CASE 2024! Congratulations to the lead author and professor/lecturer Gabriella Pizzuto, check out her awesome research in lab robotics here. Find the arxiv version of the paper here.
May 14, 2024	Are you interested in working with me as a PhD student? Then have a look at our job opening for a 4-year PhD position in Robot Learning and Representation Learning at the VU Amsterdam. Deadline is 30th of June, applications will be reviewed on a rolling basis.
Apr 29, 2024	I will be on part-time parental leave with changing patterns until November 2024. I may be slow to react to emails, review invitations etc.
Apr 29, 2024	I am co-organizer and editor for the ELLIS Robust ML & ELLIS Robust Large Language Models workshops to be held in Oxford, UK, and Helsinki, Finland. Consider attending and submitting!
Apr 05, 2024	I am a recipient of the NWO AIned XS grant provided by the Dutch Research Council and the AIned Foundation. In this projct we will be developing new methods using Large Language Models for policy generation for real-world robotics. Sounds interesting? Keep a look out for our postdoc advertisement and more details in the near future!
Apr 05, 2024	I will be giving an invited talk about our research on co-adapting robot morphology and behaviour with reinforcement learning at the EARL workshop. Are you also working on Co-Adaptation/Co-Design of robots or evolutionary robots? Consider submitting a workshop paper and let’s chat at R:SS 2024 in Delft, The Netherlands!
Feb 16, 2024	Maria Sliacka’s paper about Co-Imagination, model-based Co-Design of agent’s body and behaviour with dreaming/data-augmentation, is published by Springer. Congratulations!

selected publications

AAAI

Sparse latent space policy search

Kevin Sebastian Luck , Joni Pajarinen , Erik Berger , Ville Kyrki , and Heni Ben Amor

In Proceedings of the AAAI Conference on Artificial Intelligence , 2016

Bib PDF

@inproceedings{luck2016sparse,
  title = {Sparse latent space policy search},
  author = {Luck, Kevin Sebastian and Pajarinen, Joni and Berger, Erik and Kyrki, Ville and Amor, Heni Ben},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {30},
  number = {1},
  year = {2016},
}

R:SS

From the Lab to the Desert: Fast Prototyping and Learning of Robot Locomotion

Kevin Sebastian Luck , Joseph Campbell , Michael Jansen , Daniel Aukes , and Heni Ben Amor

In Proceedings of Robotics: Science and Systems , Jul 2017

Bib PDF

@inproceedings{Luck-RSS-17,
  author = {Luck, Kevin Sebastian and Campbell, Joseph and Jansen, Michael and Aukes, Daniel and Amor, Heni Ben},
  title = {From the Lab to the Desert: Fast Prototyping and Learning of Robot Locomotion},
  booktitle = {Proceedings of Robotics: Science and Systems},
  year = {2017},
  address = {Cambridge, Massachusetts},
  month = jul,
  doi = {10.15607/RSS.2017.XIII.075},
}

CoRL
Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning

Kevin Sebastian Luck , Heni Ben Amor , and Roberto Calandra

In Proceedings of the Conference on Robot Learning , 30 oct–01 nov 2020

Abs Bib PDF

Humans and animals are capable of quickly learning new behaviours to solve new tasks. Yet, we often forget that they also rely on a highly specialized morphology that co-adapted with motor control throughout thousands of years. Although compelling, the idea of co-adapting morphology and behaviours in robots is often unfeasible because of the long manufacturing times, and the need to redesign an appropriate controller for each morphology. In this paper, we propose a novel approach to automatically and efficiently co-adapt a robot morphology and its controller. Our approach is based on recent advances in deep reinforcement learning, and specifically the soft actor critic algorithm. Key to our approach is the possibility of leveraging previously tested morphologies and behaviors to estimate the performance of new candidate morphologies. As such, we can make full use of the information available for making more informed decisions, with the ultimate goal of achieving a more data-efficient co-adaptation (i.e., reducing the number of morphologies and behaviors tested). Simulated experiments show that our approach requires drastically less design prototypes to find good morphology-behaviour combinations, making this method particularly suitable for future co-adaptation of robot designs in the real world.
@inproceedings{pmlr-v100-luck20a, title = {Data-efficient Co-Adaptation of Morphology and Behaviour with Deep Reinforcement Learning}, author = {Luck, Kevin Sebastian and Amor, Heni Ben and Calandra, Roberto}, booktitle = {Proceedings of the Conference on Robot Learning}, pages = {854--869}, year = {2020}, editor = {Kaelbling, Leslie Pack and Kragic, Danica and Sugiura, Komei}, volume = {100}, series = {Proceedings of Machine Learning Research}, month = {30 Oct--01 Nov}, publisher = {PMLR}, url = {https://proceedings.mlr.press/v100/luck20a.html}, }

NeurIPS

Conditional Mutual Information for Disentangled Representations in Reinforcement Learning

Mhairi Dunion , Trevor McInroe , Kevin Sebastian Luck , Josiah P. Hanna , and Stefano V Albrecht

In Thirty-seventh Conference on Neural Information Processing Systems , 30 oct–01 nov 2023

Bib PDF

@inproceedings{dunion2023conditional,
  title = {Conditional Mutual Information for Disentangled Representations in Reinforcement Learning},
  author = {Dunion, Mhairi and McInroe, Trevor and Luck, Kevin Sebastian and Hanna, Josiah P. and Albrecht, Stefano V},
  booktitle = {Thirty-seventh Conference on Neural Information Processing Systems},
  year = {2023},
  url = {https://openreview.net/forum?id=EmYWJsyad4},
}

AAAI

Co-imitation: learning design and behaviour by imitation

Chang Rajani , Karol Arndt , David Blanco-Mulero , Kevin Sebastian Luck , and Ville Kyrki

In Proceedings of the AAAI Conference on Artificial Intelligence , 30 oct–01 nov 2023

Bib PDF

@inproceedings{rajani2023co,
  title = {Co-imitation: learning design and behaviour by imitation},
  author = {Rajani, Chang and Arndt, Karol and Blanco-Mulero, David and Luck, Kevin Sebastian and Kyrki, Ville},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  volume = {37},
  number = {5},
  pages = {6200--6208},
  year = {2023},
}