I have graduated and have become a post-doctoral researcher at INRIA Lille in France https://tuandam.net
Tuan Dam
Quick Info
Research Interests
Reinforcement Learning under uncertainty, Monte Carlo Tree Search, Multi Armed Bandit, POMDPs, MDPs, Information Theory, Robotics
More Information
Google Citations
Contact Information
Mail.emailtuan@robot-learning.de
Tuan is a fourth year Ph.D. researcher for the Intelligent Autonomous Systems Group at TU Darmstadt. Tuan has an interdisciplinary background in Computer Science from a bachelor's in Vietnam. Tuan did his Master's thesis in Electronics and Computer Engineering at Hanyang University, Korea. He gains lots of research experience mainly in Computer Vision, Interpreting and Understanding Deep Convolution Neural Network, Entropy Regularization Markov Decision Process, and Embedded System in Academy (ESOS lab - Korea, HMI lab - Vietnam, DFKI - Berlin, Germany, Auburn University, USA) and Industry.
During his Ph.D., Tuan is researching the development of principled methods that allow robots to operate in unstructured partially observable real-world environments. In his recent work, He proposed a framework to apply Partially Observable Markov Decision Process (POMDP) in Monte Carlo Planning settings. His work has been accepted to publish at the IJCAI 2020 conference with an acceptance rate of 12,6%. He is now focusing on bringing his framework to apply to robot planning problems such as Disentangling and Mikado Tasks.
Key References
Dam, T.; D'Eramo, C.; Peters, J.; Pajarinen, J. (submitted). A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search, Submitted to the Journal of Machine Learning Research (JMLR).
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Dam, T.; Chalvatzaki, G.; Peters, J.; Pajarinen J. (2022). Monte-Carlo Robot Path Planning, IEEE Robotics and Automation Letters, and 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
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Dam, T.; D'Eramo, C.; Peters, J.; Pajarinen J. (2021). Convex Regularization in Monte-Carlo Tree Search, Proceedings of the International Conference on Machine Learning (ICML).
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Dam, T.; Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2020). Generalized Mean Estimation in Monte-Carlo Tree Search, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).
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Supervision
- MS Thesis (co-supervised with Joni Pajarinen and Georgia Chalvatzaki), Cedric Derstroff, Memory Representations for Partially Observable Reinforcement Learning
- Robot Learning: Integrated Project (Winter 2021, co-supervised with Carlo D'Eramo), Lukas Schneider, Benchmarking advances in MCTS in Go and Chess
- Robot Learning: Integrated Project (Winter 2021, co-supervised with Georgia Chalvatzaki, and Carlo D'Eramo), Daniel Mansfeld, Alex Ruffini, Learning Laplacian Representations for continuous MCTS
- Robot Learning: Integrated Project (Winter 2019, co-supervised with Boris Belousov), Maximilian Hensel, Accelerated Mirror Descent Policy Search
!!Key References
# Fisher, B. E.;Boyd, L.;Winstein, C. J. (2006). Contralateral cerebellar damage impairs imperative planning but not updating of aimed arm movements in humans, EXPERIMENTAL BRAIN RESEARCH, 174, 3, pp.453-466, SPRINGER.
BibTeX Reference [BibTex]
Velicki, M. R.;Winstein, C. J.;Pohl, P. S. (2000). Impaired direction and extent specification of aimed arm movements in humans with stroke-related brain damage, Exp Brain Res, 130, 3, pp.362-74.
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Winstein, C. J.;Merians, A. S.;Sullivan, K. J. (1999). Motor learning after unilateral brain damage, Neuropsychologia, 37, 8, pp.975-87.
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Miyamoto, H.;Gandolfo, F.;Gomi, H.;Schaal, S.;Koike, Y.;Rieka, O.;Nakano, E.;Wada, Y.;Kawato, M. (1996). A kendama learning robot based on a dynamic optimiation principle, Preceedings of the International Conference on Neural Information Processing, pp.938-942.
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Miyamoto, H.;Schaal, S.;Gandolfo, F.;Koike, Y.;Osu, R.;Nakano, E.;Wada, Y.;Kawato, M. (1996). A Kendama learning robot based on bi-directional theory, Neural Networks, 9, 8, pp.1281-1302.
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Miyamoto, H.;Gandolfo, F.;Gomi, H.;Schaal, S.;Koike, Y.;Osu, R.;Nakano, E.;Kawato, M. (1995). A kendama learning robot based on a dynamic optimization theory, Preceedings of the 4th IEEE International Workshop on Robot and Human Communication (RO-MAN'95), pp.327-332.
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Winstein, C. J.;Pohl, P. S. (1995). Effects of unilateral brain damage on the control of goal-directed hand movements, Exp Brain Res, 105, 1, pp.163-74.
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Kawato, M.;Gandolfo, F.;Gomi, H.;Wada, Y. (1994). Teaching by showing in kendama based on optimization principle, Proceedings of the International Conference on Artificial Neural Networks (ICANN'94), 1, pp.601-606.
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Egeland, O.;Sagli, J. R.;Spangelo, I. (1991). A Damped Least-Squares Solution to Redundancy resolution, Proc. 1991 IEEE International Conference on Robotics and Automation, pp.945-950.
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Kalveram, K. T. (1991). Pattern generating and reflex-like processes controlling aiming movements in the presence of inertia, damping, and velocity, Biological Cybernetics, 64, pp.413-419.
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Brown, T. G. (1914). On the nature of the fundamental activity of the nervous centres; together with an analysis of rhythmic activity in progression, and a theory of the evolution of function in the nervous system, Journal of Physiology, London, 48, pp.18-46.
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