Getting closer: How Simulation and Humanoid League can benefit from each other. - Joschka Boedecker; Norbert Michael Mayer; Masaki Ogino; Rodrigo da Silva Guerra; Masaaki Kikuchi; Minoru Asada (AMiRE, 2005)

Flexible Coordination of Multiagent Team Behavior Using HTN Planning. - Oliver Obst; Joschka Boedecker (RoboCup, 2005)

3D2Real: Simulation League Finals in Real Robots. - Norbert Michael Mayer; Joschka Boedecker; Rodrigo da Silva Guerra; Oliver Obst; Minoru Asada (RoboCup, 2006)

Introducing Physical Visualization Sub-league. - Rodrigo da Silva Guerra; Joschka Boedecker; Norbert Michael Mayer; Shinzo Yanagimachi; Yasuji Hirosawa; Kazuhiko Yoshikawa; Masaaki Namekawa; Minoru Asada (RoboCup, 2007)

HMDP: A New Protocol for Motion Pattern Generation Towards Behavior Abstraction. - Norbert Michael Mayer; Joschka Boedecker; Kazuhiro Masui; Masaki Ogino; Minoru Asada (RoboCup, 2007)

Studies on reservoir initialization and dynamics shaping in echo state networks. - Joschka Boedecker; Oliver Obst; Norbert Michael Mayer; Minoru Asada (ESANN, 2009)

Robot motion description and real-time management with the Harmonic Motion Description Protocol. - Norbert Michael Mayer; Joschka Boedecker; Minoru Asada (Robotics Auton. Syst., 2009)

Improving Recurrent Neural Network Performance Using Transfer Entropy. - Oliver Obst; Joschka Boedecker; Minoru Asada (ICONIP (2), 2010)

Between Frustration and Elation: Sense of Control Regulates the lntrinsic Motivation for Motor Learning. - Beata J. Grzyb; Joschka Boedecker; Minoru Asada; Angel P. del Pobil; Linda B. Smith (Lifelong Learning, 2011)

Trying anyways: How ignoring the errors may help in learning new skills. - Beata J. Grzyb; Joschka Boedecker; Minoru Asada; Angel P. del Pobil; Linda B. Smith (ICDL-EPIROB, 2011)

Real-Time Inverse Dynamics Learning for Musculoskeletal Robots based on Echo State Gaussian Process Regression. - Christoph Hartmann; Joschka Boedecker; Oliver Obst; Shuhei Ikemoto; Minoru Asada (Robotics: Science and Systems, 2012)

Information processing in echo state networks at the edge of chaos. - Joschka Boedecker; Oliver Obst; Joseph T. Lizier; Norbert Michael Mayer; Minoru Asada (Theory Biosci., 2012)

Guided Self-Organization of Input-Driven Recurrent Neural Networks. - Oliver Obst; Joschka Boedecker (CoRR, 2013)

On active information storage in input-driven systems - Oliver Obst; Joschka Boedecker; Benedikt Schmidt; Minoru Asada (CoRR, 2013)

Approximate real-time optimal control based on sparse Gaussian process models. - Joschka Boedecker; Jost Tobias Springenberg; Jan Wülfing; Martin A. Riedmiller (ADPRL, 2014)

Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images. - Manuel Watter; Jost Tobias Springenberg; Joschka Boedecker; Martin A. Riedmiller (NIPS, 2015)

Autonomous Learning of State Representations for Control: An Emerging Field Aims to Autonomously Learn State Representations for Reinforcement Learning Agents from Their Real-World Sensor Observations. - Wendelin Böhmer; Jost Tobias Springenberg; Joschka Boedecker; Martin A. Riedmiller; Klaus Obermayer (Künstliche Intell., 2015)

Autonomous Optimization of Targeted Stimulation of Neuronal Networks. - Sreedhar S. Kumar; Jan Wülfing; Samora Okujeni; Joschka Boedecker; Martin A. Riedmiller; Ulrich Egert (PLoS Comput. Biol., 2016)

Uncertainty-driven Imagination for Continuous Deep Reinforcement Learning. - Gabriel Kalweit; Joschka Boedecker (CoRL, 2017)

Acting thoughts: Towards a mobile robotic service assistant for users with limited communication skills. - Felix Burget; Lukas Dominique Josef Fiederer; Daniel Kuhner; Martin Völker; Johannes Aldinger; Robin Tibor Schirrmeister; Chau Do; Joschka Boedecker; Bernhard Nebel; Tonio Ball; Wolfram Burgard (ECMR, 2017)

Predicting Time Series with Space-Time Convolutional and Recurrent Neural Networks. - Wolfgang Groß; Sascha Lange; Joschka Bödecker; Manuel Blum 002 (ESANN, 2017)

Deep reinforcement learning with successor features for navigation across similar environments. - Jingwei Zhang 001; Jost Tobias Springenberg; Joschka Boedecker; Wolfram Burgard (IROS, 2017)

Neural SLAM. - Jingwei Zhang 001; Lei Tai; Joschka Boedecker; Wolfram Burgard; Ming Liu 001 (CoRR, 2017)

Hardware Implementation of a Performance and Energy-optimized Convolutional Neural Network for Seizure Detection. - Simon Heller; Maria Hügle; Iman Nematollahi; Farrokh Manzouri; Matthias Dümpelmann; Andreas Schulze-Bonhage; Joschka Boedecker; Peter Woias (EMBC, 2018)

Controlling biological neural networks with deep reinforcement learning. - Jan Wülfing; Sreedhar S. Kumar; Joschka Boedecker; Martin A. Riedmiller; Ulrich Egert (ESANN, 2018)

Prediction of electrocardiography features points using seismocardiography data: a machine learning approach. - Robert Dürichen; Keshav Deep Verma; Seow Yuen Yee; Thomas Rocznik; Philip Schmidt 001; Joschka Boedecker; Christian Peters (UbiComp, 2018)

Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller. - Maria Hügle; Simon Heller; Manuel Watter; Manuel Blum 002; Farrokh Manzouri; Matthias Dümpelmann; Andreas Schulze-Bonhage; Peter Woias; Joschka Boedecker (IJCNN, 2018)

High-level Decision Making for Safe and Reasonable Autonomous Lane Changing using Reinforcement Learning. - Branka Mirchevska; Christian Pek; Moritz Werling; Matthias Althoff; Joschka Boedecker (ITSC, 2018)

VR Goggles for Robots: Real-to-sim Domain Adaptation for Visual Control. - Jingwei Zhang 001; Lei Tai; Yufeng Xiong; Ming Liu 001; Joschka Boedecker; Wolfram Burgard (CoRR, 2018)

Multimodal Spatio-Temporal Information in End-to-End Networks for Automotive Steering Prediction. - Mohamed Abou-Hussein; Stefan H. Müller; Joschka Boedecker (ICRA, 2019)

Dynamic Input for Deep Reinforcement Learning in Autonomous Driving. - Maria Hügle; Gabriel Kalweit; Branka Mirchevska; Moritz Werling; Joschka Boedecker (IROS, 2019)

Scheduled Intrinsic Drive: A Hierarchical Take on Intrinsically Motivated Exploration. - Jingwei Zhang 001; Niklas Wetzel; Nicolai Dorka; Joschka Boedecker; Wolfram Burgard (CoRR, 2019)

Learning-based Model Predictive Control for Safe Exploration and Reinforcement Learning. - Torsten Koller; Felix Berkenkamp; Matteo Turchetta; Joschka Boedecker; Andreas Krause 001 (CoRR, 2019)

Off-policy Multi-step Q-learning. - Gabriel Kalweit; Maria Hügle; Joschka Boedecker (CoRR, 2019)

Hybrid Brain-Computer-Interfacing for Human-Compliant Robots: Inferring Continuous Subjective Ratings With Deep Regression. - Lukas Dominique Josef Fiederer; Martin Völker; Robin Tibor Schirrmeister; Wolfram Burgard; Joschka Boedecker; Tonio Ball (Frontiers Neurorobotics, 2019)

Adaptive long-term control of biological neural networks with Deep Reinforcement Learning. - Jan M. Wülfing; Sreedhar S. Kumar; Joschka Boedecker; Martin A. Riedmiller; Ulrich Egert (Neurocomputing, 2019)

VR-Goggles for Robots: Real-to-Sim Domain Adaptation for Visual Control. - Jingwei Zhang 001; Lei Tai; Peng Yun; Yufeng Xiong; Ming Liu 001; Joschka Boedecker; Wolfram Burgard (IEEE Robotics Autom. Lett., 2019)

A service assistant combining autonomous robotics, flexible goal formulation, and deep-learning-based brain-computer interfacing. - Daniel Kuhner; Lukas Dominique Josef Fiederer; Johannes Aldinger; Felix Burget; Martin Völker; Robin Tibor Schirrmeister; Chau Do; Joschka Boedecker; Bernhard Nebel; Tonio Ball; Wolfram Burgard (Robotics Auton. Syst., 2019)

Dynamic Interaction-Aware Scene Understanding for Reinforcement Learning in Autonomous Driving. - Maria Hügle; Gabriel Kalweit; Moritz Werling; Joschka Boedecker (ICRA, 2020)

Learning Human-Aware Robot Navigation from Physical Interaction via Inverse Reinforcement Learning. - Marina Kollmitz; Torsten Koller; Joschka Boedecker; Wolfram Burgard (IROS, 2020)

Deep Inverse Q-learning with Constraints. - Gabriel Kalweit; Maria Hügle; Moritz Werling; Joschka Boedecker (NeurIPS, 2020)

Interpretable Multi Time-scale Constraints in Model-free Deep Reinforcement Learning for Autonomous Driving. - Gabriel Kalweit; Maria Hügle; Moritz Werling; Joschka Boedecker (CoRR, 2020)

A Dynamic Deep Neural Network For Multimodal Clinical Data Analysis. - Maria Hügle; Gabriel Kalweit; Thomas Huegle; Joschka Boedecker (CoRR, 2020)

Machine-learning-based diagnostics of EEG pathology. - Lukas Alexander Wilhelm Gemein; Robin Tibor Schirrmeister; Patryk Chrabaszcz; Daniel Wilson 003; Joschka Boedecker; Andreas Schulze-Bonhage; Frank Hutter; Tonio Ball (NeuroImage, 2020)

Amortized Q-learning with Model-based Action Proposals for Autonomous Driving on Highways. - Branka Mirchevska; Maria Hügle; Gabriel Kalweit; Moritz Werling; Joschka Boedecker (ICRA, 2021)

AnyNets: Adaptive Deep Neural Networks for Medical Data with Missing Values. - Maria Kalweit; Gabriel Kalweit; Joschka Boedecker (AI4Function@IJCAI, 2021)

Q-learning with Long-term Action-space Shaping to Model Complex Behavior for Autonomous Lane Changes. - Gabriel Kalweit; Maria Hügle; Moritz Werling; Joschka Boedecker (IROS, 2021)

Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty. - Alireza Ranjbar; Ngo Anh Vien; Hanna Ziesche; Joschka Boedecker; Gerhard Neumann (IROS, 2021)

Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning. - Nicolai Dorka; Joschka Boedecker; Wolfram Burgard (CoRR, 2021)

Latent Plans for Task-Agnostic Offline Reinforcement Learning. - Erick Rosete-Beas; Oier Mees; Gabriel Kalweit; Joschka Boedecker; Wolfram Burgard (CoRL, 2022)

Affordance Learning from Play for Sample-Efficient Policy Learning. - Jessica Borja-Diaz; Oier Mees; Gabriel Kalweit; Lukás Hermann; Joschka Boedecker; Wolfram Burgard (ICRA, 2022)

Deep Surrogate Q-Learning for Autonomous Driving. - Maria Kalweit; Gabriel Kalweit; Moritz Werling; Joschka Boedecker (ICRA, 2022)

Optimizing Trajectories for Highway Driving with Offline Reinforcement Learning. - Branka Mirchevska; Moritz Werling; Joschka Boedecker (CoRR, 2022)

On the calibration of underrepresented classes in LiDAR-based semantic segmentation. - Mariella Dreissig; Florian Piewak; Joschka Boedecker (CoRR, 2022)

Correct Me If I am Wrong: Interactive Learning for Robotic Manipulation. - Eugenio Chisari; Tim Welschehold; Joschka Boedecker; Wolfram Burgard; Abhinav Valada (IEEE Robotics Autom. Lett., 2022)

Robust and Data-efficient Q-learning by Composite Value-estimation. - Gabriel Kalweit; Maria Kalweit; Joschka Boedecker (Trans. Mach. Learn. Res., 2022)

Imitation Learning from Nonlinear MPC via the Exact Q-Loss and its Gauss-Newton Approximation. - Andrea Ghezzi; Jasper Hoffmann; Jonathan Frey; Joschka Boedecker; Moritz Diehl (CDC, 2023)

Robust Reinforcement Learning in Continuous Control Tasks with Uncertainty Set Regularization. - Yuan Zhang 027; Jianhong Wang; Joschka Boedecker (CoRL, 2023)

Context-Conditional Navigation with a Learning-Based Terrain- and Robot-Aware Dynamics Model. - Suresh Guttikonda; Jan Achterhold; Haolong Li; Joschka Boedecker; Joerg Stueckler (ECMR, 2023)

A Hierarchical Approach for Strategic Motion Planning in Autonomous Racing. - Rudolf Reiter; Jasper Hoffmann; Joschka Boedecker; Moritz Diehl (ECC, 2023)

On the Calibration of Uncertainty Estimation in LiDAR-Based Semantic Segmentation. - Mariella Dreissig; Florian Piewak; Joschka Boedecker (ITSC, 2023)

Survey on LiDAR Perception in Adverse Weather Conditions. - Mariella Dreissig; Dominik Scheuble; Florian Piewak; Joschka Boedecker (IV, 2023)

Incorporating Recurrent Reinforcement Learning into Model Predictive Control for Adaptive Control in Autonomous Driving. - Yuan Zhang 027; Joschka Boedecker; Chuxuan Li; Guyue Zhou (CoRR, 2023)

Robust Tumor Detection from Coarse Annotations via Multi-Magnification Ensembles. - Mehdi Naouar; Gabriel Kalweit; Ignacio Mastroleo; Philipp Poxleitner; Marc Christian Metzger; Joschka Boedecker; Maria Kalweit (CoRR, 2023)

Geometric Regularity with Robot Intrinsic Symmetry in Reinforcement Learning. - Shengchao Yan; Yuan Zhang 027; Baohe Zhang; Joschka Boedecker; Wolfram Burgard (CoRR, 2023)

Brain Age Revisited: Investigating the State vs. Trait Hypotheses of EEG-derived Brain-Age Dynamics with Deep Learning. - Lukas Alexander Wilhelm Gemein; Robin Tibor Schirrmeister; Joschka Boedecker; Tonio Ball (CoRR, 2023)

L(M)V-IQL: Multiple Intention Inverse Reinforcement Learning for Animal Behavior Characterization. - Hao Zhu; Brice De La Crompe; Gabriel Kalweit; Artur Schneider; Maria Kalweit; Ilka Diester; Joschka Boedecker (CoRR, 2023)

CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations. - Mehdi Naouar; Gabriel Kalweit; Anusha Klett; Yannick Vogt; Paula Silvestrini; Diana Laura Infante Ramírez; Roland Mertelsmann; Joschka Boedecker; Maria Kalweit (CoRR, 2023)

Patient groups in Rheumatoid arthritis identified by deep learning respond differently to biologic or targeted synthetic DMARDs. - Maria Kalweit; Andrea M. Burden; Joschka Boedecker; Thomas Hügle; Theresa Burkard (PLoS Comput. Biol., 2023)

Adaptively Calibrated Critic Estimates for Deep Reinforcement Learning. - Nicolai Dorka; Tim Welschehold; Joschka Bödecker; Wolfram Burgard (IEEE Robotics Autom. Lett., 2023)

The Treachery of Images: Bayesian Scene Keypoints for Deep Policy Learning in Robotic Manipulation. - Jan Ole von Hartz; Eugenio Chisari; Tim Welschehold; Wolfram Burgard; Joschka Boedecker; Abhinav Valada (IEEE Robotics Autom. Lett., 2023)

UDUC: An Uncertainty-Driven Approach for Learning-Based Robust Control. - Yuan Zhang 027; Jasper Hoffmann; Joschka Boedecker (ECAI, 2024)

Improving the Efficiency and Efficacy of Multi-Agent Reinforcement Learning on Complex Railway Networks with a Local-Critic Approach. - Yuan Zhang 027; Umashankar Deekshith; Jianhong Wang; Joschka Boedecker (ICAPS, 2024)

Learning Continuous Control with Geometric Regularity from Robot Intrinsic Symmetry. - Shengchao Yan; Baohe Zhang; Yuan Zhang 027; Joschka Boedecker; Wolfram Burgard (ICRA, 2024)

Safe Imitation Learning of Nonlinear Model Predictive Control for Flexible Robots. - Shamil Mamedov; Rudolf Reiter; Seyed Mahdi B. Azad; Ruan Viljoen; Joschka Boedecker; Moritz Diehl; Jan Swevers (IROS, 2024)

PlanNetX: Learning an efficient neural network planner from MPC for longitudinal control. - Jasper Hoffmann; Diego Fernandez Clausen; Julien Brosseit; Julian Bernhard; Klemens Esterle; Moritz Werling; Michael Karg; Joschka Bödecker (L4DC, 2024)

The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning. - Moritz Schneider; Robert Krug 002; Narunas Vaskevicius; Luigi Palmieri; Joschka Boedecker (NeurIPS, 2024)

Reaching the ceiling? Empirical scaling behaviour for deep EEG pathology classification. - Ann-Kathrin Kiessner; Robin Tibor Schirrmeister; Joschka Boedecker; Tonio Ball (Comput. Biol. Medicine, 2024)

Stable Online and Offline Reinforcement Learning for Antibody CDRH3 Design. - Yannick Vogt; Mehdi Naouar; Maria Kalweit; Christoph Cornelius Miething; Justus Duyster; Roland Mertelsmann; Gabriel Kalweit; Joschka Boedecker (CoRR, 2024)

Constrained Reinforcement Learning with Smoothed Log Barrier Function. - Baohe Zhang; Yuan Zhang 027; Lilli Frison; Thomas Brox; Joschka Bödecker (CoRR, 2024)

Hierarchical Insights: Exploiting Structural Similarities for Reliable 3D Semantic Segmentation. - Mariella Dreissig; Florian Piewak; Joschka Boedecker (CoRR, 2024)

Latent Linear Quadratic Regulator for Robotic Control Tasks. - Yuan Zhang 027; Shaohui Yang; Toshiyuki Ohtsuka; Colin N. Jones; Joschka Boedecker (CoRR, 2024)

Advances in Land Surface Model-based Forecasting: A comparative study of LSTM, Gradient Boosting, and Feedforward Neural Network Models as prognostic state emulators. - Marieke Wesselkamp; Matthew Chantry; Ewan Pinnington; Margarita Choulga; Souhail Boussetta; Maria Kalweit; Joschka Boedecker; Carsten F. Dormann; Florian Pappenberger; Gianpaolo Balsamo (CoRR, 2024)

Revisiting Safe Exploration in Safe Reinforcement learning. - David Eckel; Baohe Zhang; Joschka Bödecker (CoRR, 2024)

BetterBodies: Reinforcement Learning guided Diffusion for Antibody Sequence Design. - Yannick Vogt; Mehdi Naouar; Maria Kalweit; Christoph Cornelius Miething; Justus Duyster; Joschka Boedecker; Gabriel Kalweit (CoRR, 2024)

Constrained Reinforcement Learning for Safe Heat Pump Control. - Baohe Zhang; Lilli Frison; Thomas Brox; Joschka Bödecker (CoRR, 2024)

Multi-intention Inverse Q-learning for Interpretable Behavior Representation. - Hao Zhu; Brice De La Crompe; Gabriel Kalweit; Artur Schneider; Maria Kalweit; Ilka Diester; Joschka Boedecker (Trans. Mach. Learn. Res., 2024)

The Art of Imitation: Learning Long-Horizon Manipulation Tasks From Few Demonstrations. - Jan Ole von Hartz; Tim Welschehold; Abhinav Valada; Joschka Boedecker (IEEE Robotics Autom. Lett., 2024)

Salvage: Shapley-distribution Approximation Learning Via Attribution Guided Exploration for Explainable Image Classification. - Mehdi Naouar; Hanne Raum; Jens Rahnfeld; Yannick Vogt; Joschka Boedecker; Gabriel Kalweit; Maria Kalweit (ICLR, 2025)

SR-Reward: Taking The Path More Traveled. - Seyed Mahdi B. Azad; Zahra Padar; Gabriel Kalweit; Joschka Boedecker (Trans. Mach. Learn. Res., 2025)

Inverse Reinforcement Learning via Convex Optimization. - Hao Zhu; Yuan Zhang 027; Joschka Boedecker (CoRR, 2025)

Solving Inverse Problem for Multi-armed Bandits via Convex Optimization. - Hao Zhu; Joschka Boedecker (CoRR, 2025)

Synthesis of Model Predictive Control and Reinforcement Learning: Survey and Classification. - Rudolf Reiter; Jasper Hoffmann; Dirk Reinhardt; Florian Messerer; Katrin Baumgärtner; Shamburaj Sawant; Joschka Boedecker; Moritz Diehl; Sebastien Gros (CoRR, 2025)

Multi-convex Programming for Discrete Latent Factor Models Prototyping. - Hao Zhu; Shengchao Yan; Jasper Hoffmann; Joschka Boedecker (CoRR, 2025)

The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning. - Jan Ole von Hartz; Adrian Röfer; Joschka Boedecker; Abhinav Valada (CoRR, 2025)

Fast ECoT: Efficient Embodied Chain-of-Thought via Thoughts Reuse. - Zhekai Duan; Yuan Zhang; Shikai Geng; Gaowen Liu; Joschka Boedecker; Chris Xiaoxuan Lu (CoRR, 2025)