Donders Institute for Brain, Cognition and Behaviour
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Theme 4: Brain Networks and Neuronal Communication

Foundations of Intelligent Technology (FoundIT)

The group studies the foundations of intelligent behaviour in technology and artificial agents, including, for example, social and industrial robots, and autonomous vehicles.
On the theoretical end, we work on embodiment and theories within embodied cognitive science, including their applicability to, and consequences for artificial agents. We also design and implement novel algorithms for the control of such agents in societally relevant applications, with a particular current focus on spiking neural network and neuromorphic approaches, as well as work on deep active inference. On the more applied end, we study how humans (want to) interact with such technology, and what the consequences are for the development of these agents.
The group manages the RobotLab at the Department of AI, which includes several state of the art robots including a Pepper, several Naos and drones, and a UR5e.
Contact
Name: Serge Thill
Telephone: 024-3615981
Email: s.thill@donders.ru.nl
Visiting address: Donders Centre for Cognition
Thomas van Aquinostraat 4
6525 GD NIJMEGEN
The Netherlands
Postal address: Donders Centre for Cognition
P.O. Box 9104
6500 HE Nijmegen
The Netherlands

Key publications

Windridge, D., Svensson, H. & Thill, S. (2020). On the utility of dreaming: A general model for how learning in artificial agents can benefit from data hallucination. Adaptive Behavior. doi: 10.1177/1059712319896489


Zanatto, D., Patacchiola, M., Goslin, J., Thill, S. & Cangelosi, A. (2020). Do humans imitate robots? An investigation of strategic social learning in human-robot interaction. In HRI 2020: Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction (pp. 449-457). Cambridge: Association for Computing Machinery (ACM) doi: 10.1145/3319502.3374776


Lanillos, P., Oliva, D., Philippsen, A., Yamashita, Y., Nagai, Y., & Cheng, G. (2020). A review on neural network models of schizophrenia and autism spectrum disorder. Neural Networks, 122, 338-363.


Cao, H.L., Esteban, P.G., Bartlett, M.E., Baxter, P.E., Belpaeme, T., Billing, E.A., . . . Thill, S., Zhou, X. & Ziemke, T. (2019). Robot-enhanced therapy: Development and validation of supervised autonomous robotic system for autism spectrum disorders therapy. IEEE Robotics and Automation Magazine, 26 (2), 49-58. doi: 10.1109/MRA.2019.2904121


Windridge, D. & Thill, S. (2018). Representational fluidity in embodied (artificial) cognition. Biosystems, 172, 9-17. doi: 10.1016/j.biosystems.2018.07.007


Lanillos, P., & Cheng, G. (2018, October). Adaptive robot body learning and estimation through predictive coding. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 4083-4090). IEEE.


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Theme 4:
Natural Computing & Neurotechnology

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Research Group
Foundations of Intelligent Technology (FoundIT)

Principal Investigator
Dr. Serge Thill (Associate Professor)

Group members

Senior Staff
Pablo Lanillos (Assistant Professor)
Mahyar Shahsavari (Assistant Professor)

Postdoc

Dr. Ruben R. van Bergen
Ajith Anil Meera
Marcos Bueno

PhD student
Justus Hübotter