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 The Multi-disciplinary Conference on Reinforcement Learning and Decision Making, USA, 2017 [unpublished]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