Publications
Here is a list of my publications and some other documents in chronological order across my different projects.
You can find more information about specific projects on my research page.
Papers
Ballou A., Alameda-Pineda X., Reinke C.: Variational Meta Reinforcement Learning for Social Robotics. Applied Intelligence, (DOI: 10.100/s10489-023-04691-5), 2023
Reinke C., Alameda-Pineda X.: Successor Feature Representations. Transactions on Machine Learning Research, 2023
Emukpere D., Alameda-Pineda X., Reinke, C.: Successor Feature Neural Episodic Control. Presented at Fifth Workshop on Meta-Learning at NeurIPS (arXiv:2111.03110), 2021
Reinke C., Etcheverry M., Oudeyer PY.: Intrinsically Motivated Exploration for Automated Discovery of Patterns in Morphogenetic Systems. International Conference on Learning Representations (ICLR), 2020
Reinke C.: Time Adaptive Reinforcement Learning. Presented at ICLR Workshop: Beyond Tabula Rasa in Reinforcement Learning (arXiv: 2004.08600), 2020
Etcheverry M., Oudeyer PY., Reinke C.: Progressive Growing of Self-Organized Hierarchical Representations for Exploration. Presented at ICLR workshop: Beyond Tabula Rasa in Reinforcement Learning (arXiv:2005.06369), 2020
Reinke C., Uchibe E., Doya K.: Average Reward Optimization with Multiple Discounting Reinforcement Learners. Proceedings of the 2017 International Conference on Neural Information Processing (ICONIP), 2017 (DOI: 10.1007/97b8-3-319-70087-8_81)
Reinke C., Doya K.: Adaptation of Optimization Algorithms to Problem Domains by Transfer Learning. Proceedings of the 2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), pp. 214-215, (DOI: 10.1109/ICIIBMS.2017.8279737), 2017
Reinke C., Uchibe E., Doya K.; Fast Adaptation of Behavior to Changing Goals with a Gamma Ensemble. The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, USA, 2017 [unpublished]
Reinke C., Uchibe E., Doya K.: Maximizing the Average Reward in Episodic Reinforcement Learning Tasks. Proceedings of the 2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), pp. 420-421, (DOI: 10.1109/ICIIBMS.2015.7439495), 2015
Theses
Ph.D. Thesis: The Gamma-Ensemble - Adaptive Reinforcement Learning via Modular Discounting, Okinawa Institute of Science and Technology Graduate University, 2018
Master Thesis: Problem-Specific Adaptation of Optimization Algorithms, University of Osnabrück, 2012
Bachelor Thesis: Automated Identification of Motor Models for a Humanoid Robot, University of Osnabrück, 2010
Technical Reports
A Critical View on Model-free / Model-based Decision Learning, Okinawa Institute of Science and Technology, 2014
Artificial Evolution of a Walking Controller for a Robot Dog, Okinawa Institute of Science and Technology, 2011
Posters
Patil B., Alameda-Pineda X., Reinke C.: Brain-Inspired Deep Neural Layers for Low-Dimensional Inputs: Univariate Radial Basis Function Layers, Eleventh Symposium on Biology of Decision Making (SBDM), France, 2023
Reinke C., Uchibe E., Doya K.: Fast Adaptation of Behavior to Changing Goals with a Gamma Ensemble, The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, USA, 2017
Reinke C., Uchibe E., Doya K.: From Neuroscience to Artificial Intelligence: Maximizing Average Reward in Episodic Reinforcement Learning Tasks with an Ensemble of Q-Learners, The Third CiNet Conference: Neural mechanisms of decision making, Japan, 2016
Reinke C., Uchibe E., Doya K.: Learning of Stress Adaptive Habits with an Ensemble of Q-Learners, The 2nd International Workshop on Cognitive Neuroscience Robotics, Japan, 2016
Reinke C., Uchibe E., Doya K.: Maximizing the Average Reward in Episodic Reinforcement Learning Tasks with an Ensemble of Q-Learners, International Symposium on Prediction and Decision Making, University of Tokyo, Japan, 2015
Reinke C., Uchibe E., Doya K.: Gamma-QCL: Learning Multiple Goals with a Gamma-submodular Model-free Reinforcement Learning Framework, The 15th Winter Workshop on Mechanism of Brain and Mind, Japan, 2015
Reinke C., Uchibe E.; Doya K.: A Critical View on the Model based/Model free Learning Theory, The 7th Research Area Meeting Grant-in Aid for Scientific Research on Innovative Areas: Elucidation of the Neural Computation for Prediction and Decision Making, Japan, 2014
Reinke C.: Automated Identification of Motor Models for a Humanoid Robot, Interdisciplinary College Günne, Germany, 2010