Robert Lange
Photo: SCIoI
Robert Tjarko Lange works at the intersection of machine learning and behavioral biology.
He joined SCIoI as a doctoral researcher in October 2019.
Robert’s research combines tools from top-down optimization, such as Reinforcement Learning, with bottom-up phenomenological modeling. Thereby, nature and nurture are analyzed from a complementary perspective and not as forces that trade off. Before joining SCIoI, he obtained an M.Sc. in Computing from Imperial College London and conducted research within the Einstein Center for Neurosciences Berlin.
Projects
Robert Lange is member of:
Publications +
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19921
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Lange, A. L., Ackermann, H., Lazarides, R., & Hafner, V. V. (2027). A Robot-LLM Integration Framework for Social Learning Interactions. In O. Brock, J. Krichmar, & V. Mengers (Eds.), From Animals to Animats 18 (Vol. 16965, pp. 180–191). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-39953-3_15
Ackermann, H., Lange, A. L., Dumont, H., Hafner, V. V., & Lazarides, R. (2026). Real-time cognitive-affective dynamics of failure feedback in a technology-based learning task. Communications Psychology, 4(1), 95. https://doi.org/10.1038/s44271-026-00487-8
Ackermann, H., Lange, A. L., Hafner, V. V., & Lazarides, R. (2025). How adaptive social robots influence cognitive, emotional, and self-regulated learning. Scientific Reports, 15(1), 6581. https://doi.org/10.1038/s41598-025-91236-0
Taliaronak, V., Lange, A. L., Kirtay, M., Oztop, E., & Hafner, V. V. (2023). Advancing Humanoid Robots for Social Integration: Evaluating Trustworthiness Through a Social Cognitive Framework. 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2112–2119. https://doi.org/10.1109/RO-MAN57019.2023.10309519
Gómez-Nava, L., Lange, R. T., Klamser, P. P., Lukas, J., Arias-Rodriguez, L., Bierbach, D., Krause, J., Sprekeler, H., & Romanczuk, P. (2023). Fish shoals resemble a stochastic excitable system driven by environmental perturbations. Nature Physics, 19(5), 663–669. https://doi.org/10.1038/s41567-022-01916-1
Lange, R. T., & Sprekeler, H. (2022). Learning Not to Learn: Nature versus Nurture In Silico. Proceedings of the AAAI Conference on Artificial Intelligence, 36(7), 7290–7299. https://doi.org/10.1609/aaai.v36i7.20691
Vischer, M., Lange, R. T., & Sprekeler, H. (2022). On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning. International Conference on Learning Representations (ICLR). https://doi.org/10.48550/arXiv.2105.01648
Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O., Abdel Rahman, R., Hafner, V. V., Kuhlen, A. K., & Haynes, J.-D. (2021). Who is my interlocutor? Partner-specific neural representations during communicative interactions with human or artificial task partners. [Poster]. 5th Virtual Social Interactions (VSI) Conference.
Pischedda, D., Lange, A., Kirtay, M., Wudarczyk, O., Abdel Rahman, R., Hafner, V. V., Kuhlen, A. K., & Haynes, J.-D. (2021). Am I speaking to a human, a robot, or a computer? Neural representations of task partners in communicative interactions with humans or artificial agents [Poster]. Annual Meeting of the Society for Neuroscience (SfN).
G-Research Grant for PhD Students, Robert Tjarko Lange (2023) More information
G-Research Grant for PhD Students in a Quantitative Field, Robert Tjarko Lange (2023) More information
Student Travel Award (GECCO 2023 Conference), Robert Tjarko Lange (2023)
