Martin A. Riedmiller

Jan Mattner, Sascha Lange, Martin Riedmiller: Learn to Swing Up and Balance a Real Pole Based on Raw Visual Input Data. ICONIP (5) 2012: 126-133

Jost Tobias Springenberg, Martin Riedmiller: Learning Temporal Coherent Features through Life-Time Sparsity. ICONIP (1) 2012: 347-356

Manuel Blum, Jost Tobias Springenberg, Jan Wülfing, Martin Riedmiller: A learned feature descriptor for object recognition in RGB-D data. ICRA 2012: 1298-1303

Sascha Lange, Martin Riedmiller, Arne Voigtländer: Autonomous reinforcement learning on raw visual input data in a real world application. IJCNN 2012: 1-8

Oliver Obst, Martin Riedmiller: Taming the reservoir: Feedforward training for recurrent neural networks. IJCNN 2012: 1-7

Jan Wülfing, Martin Riedmiller: Unsupervised Learning of Local Features for Music Classification. ISMIR 2012: 139-144

Roland Hafner, Martin Riedmiller: Reinforcement learning in feedback control - Challenges and benchmarks from technical process control. Machine Learning 84(1-2): 137-169 (2011)

Martin Lauer, Roland Hafner, Sascha Lange, Martin Riedmiller: Cognitive concepts in autonomous soccer playing robots. Cognitive Systems Research 11(3): 287-309 (2010)

Sascha Lange, Martin Riedmiller: Deep learning of visual control policies. ESANN 2010

Sascha Lange, Martin Riedmiller: Deep auto-encoder neural networks in reinforcement learning. IJCNN 2010: 1-8

Thomas Gabel, Martin Riedmiller: On Progress in RoboCup: The Simulation League Showcase. RobuCup 2010: 36-47

Martin Riedmiller, Thomas Gabel, Roland Hafner, Sascha Lange: Reinforcement learning for robot soccer. Auton. Robots 27(1): 55-73 (2009)

Tim C. Kietzmann, Sascha Lange, Martin A. Riedmiller: Computational object recognition: a biologically motivated approach. Biological Cybernetics 100(1): 59-79 (2009)

Tim C. Kietzmann, Martin Riedmiller: The Neuro Slot Car Racer: Reinforcement Learning in a Real World Setting. ICMLA 2009: 311-316

Thomas Gabel, Martin A. Riedmiller: Reinforcement learning for DEC-MDPs with changing action sets and partially ordered dependencies. AAMAS (3) 2008: 1333-1336

Thomas Gabel, Martin Riedmiller: Increasing Precision of Credible Case-Based Inference. ECCBR 2008: 225-239

Thomas Gabel, Martin Riedmiller: Evaluation of Batch-Mode Reinforcement Learning Methods for Solving DEC-MDPs with Changing Action Sets. EWRL 2008: 82-95

Martin A. Riedmiller, Roland Hafner, Sascha Lange, Martin Lauer: Learning to dribble on a real robot by success and failure. ICRA 2008: 2207-2208

Thomas Gabel, Martin A. Riedmiller: Joint Equilibrium Policy Search for Multi-Agent Scheduling Problems. MATES 2008: 61-72

Thomas Gabel, Martin A. Riedmiller, Florian Trost: A Case Study on Improving Defense Behavior in Soccer Simulation 2D: The NeuroHassle Approach. RoboCup 2008: 61-72

Martin A. Riedmiller, Thomas Gabel: On Experiences in a Complex and Competitive Gaming Domain: Reinforcement Learning Meets RoboCup. CIG 2007: 17-23

Stephan Timmer, Martin Riedmiller: Safe Q-Learning on Complete History Spaces. ECML 2007: 394-405

Arne Voigtländer, Sascha Lange, Martin Lauer, Martin A. Riedmiller: Real-time 3D Ball Recognition using Perspective and Catadioptric Cameras. EMCR 2007

Verena Heidrich-Meisner, Martin Lauer, Christian Igel, Martin A. Riedmiller: Reinforcement learning in a nutshell. ESANN 2007: 277-288

Martin Riedmiller, Michael Montemerlo, Hendrik Dahlkamp: Learning to Drive a Real Car in 20 Minutes. FBIT 2007: 645-650

Thomas Gabel, Martin Riedmiller: An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs. ICCBR 2007: 344-358

Roland Hafner, Martin Riedmiller: Neural Reinforcement Learning Controllers for a Real Robot Application. ICRA 2007: 2098-2103

Heiko Müller, Martin Lauer, Roland Hafner, Sascha Lange, Artur Merke, Martin Riedmiller: Making a Robot Learn to Play Soccer Using Reward and Punishment. KI 2007: 220-234

Martin A. Riedmiller, Thomas Gabel, Roland Hafner, Sascha Lange, Martin Lauer: Die Brainstormers: Entwurfsprinzipien lernfähiger autonomer Roboter. Informatik Spektrum 29(3): 175-190 (2006)

Thomas Gabel, Martin A. Riedmiller: Learning a Partial Behavior for a Competitive Robotic Soccer Agent. KI 20(2): 18-23 (2006)

Thomas Gabel, Martin Riedmiller: Reducing policy degradation in neuro-dynamic programming. ESANN 2006: 653-658

Thomas Gabel, Martin Riedmiller: Multi-agent Case-Based Reasoning for Cooperative Reinforcement Learners. ECCBR 2006: 32-46

Sascha Lange, Martin Riedmiller: Appearance-Based Robot Discrimination Using Eigenimages. RoboCup 2006: 499-506

Martin A. Riedmiller, Daniel Withopf: Effective Methods for Reinforcement Learning in Large Multi-Agent Domains. it - Information Technology 47(5): 241-249 (2005)

Martin Riedmiller: Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method. ECML 2005: 317-328

Thomas Gabel, Martin A. Riedmiller: CBR for State Value Function Approximation in Reinforcement Learning. ICCBR 2005: 206-221

Martin Lauer, Sascha Lange, Martin A. Riedmiller: Modeling Moving Objects in a Dynamically Changing Robot Application. KI 2005: 291-303

Alexander Sung, Artur Merke, Martin A. Riedmiller: Reinforcement Learning Using a Grid Based Function Approximator. Biomimetic Neural Learning for Intelligent Robots 2005: 235-244

Martin Lauer, Sascha Lange, Martin Riedmiller: Calculating the Perfect Match: An Efficient and Accurate Approach for Robot Self-localization. RoboCup 2005: 142-153

Stephan Timmer, Martin Riedmiller: Learning policies for abstract state spaces. SMC 2005: 3179-3184

Martin Riedmiller, Daniel Withopf: Comparing different methods to speed up reinforcement learning in a complex domain. SMC 2005: 3185-3190

Martin Riedmiller: Neural reinforcement learning to swing-up and balance a real pole. SMC 2005: 3191-3196

Daniele Nardi, Martin Riedmiller, Claude Sammut, José Santos-Victor (Eds.): RoboCup 2004: Robot Soccer World Cup VIII. Lecture Notes in Computer Science 3276, Springer 2005, isbn 3-540-25046-8

Enrico Pagello, Emanuele Menegatti, Ansgar Bredenfeld, Paulo Costa, Thomas Christaller, Adam Jacoff, Daniel Polani, Martin Riedmiller, Alessandro Saffiotti, Elizabeth Sklar, Takashi Tomoichi: RoboCup-2003: New Scientific and Technical Advances. AI Magazine 25(2): 81-98 (2004)

Martin Riedmiller, François Fages, Malik Ghallab, Wolfgang Wahlster, Jörg H. Siekmann: Invited talks. KI 18(3): 44- (2004)

Ralf Schoknecht, Martin Spott, Martin A. Riedmiller: Fynesse: An architecture for integrating prior knowledge in autonomously learning agents. Soft Comput. 8(6): 397-408 (2004)

Martin Lauer, Martin Riedmiller: Reinforcement Learning for Stochastic Cooperative Multi-Agent Systems. AAMAS 2004: 1516-1517

Martin Riedmiller: Machine Learning for Autonomous Robots. KI 2004: 52-55

Sascha Lange, Martin Riedmiller: Evolution of Computer Vision Subsystems in Robot Navigation and Image Classification Tasks. RobuCup 2004: 184-195

Ralf Schoknecht, Martin Riedmiller: Reinforcement learning on explicitly specified time scales. Neural Computing and Applications 12(2): 61-80 (2003)

Ralf Schoknecht, Martin A. Riedmiller: Learning to Control at Multiple Time Scales. ICANN 2003: 479-487

Martin Lauer, Martin A. Riedmiller, Thomas Ragg, Walter Baum, Michael Wigbers: The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction. IDA 2003: 451-461

Roland Hafner, Martin Riedmiller: Reinforcement learning on an omnidirectional mobile robot. IROS 2003: 418-423

Enrico Pagello, Emanuele Menegatti, Ansgar Bredenfeld, Paulo Costa, Thomas Christaller, Adam Jacoff, Jeffrey Johnson, Martin Riedmiller, Alessandro Saffiotti, Takashi Tomoichi: Overview of RoboCup 2003 Competition and Conferences. RoboCup 2003: 1-14

Hans-Dieter Burkhard, Minoru Asada, Andrea Bonarini, Adam Jacoff, Daniele Nardi, Martin Riedmiller, Claude Sammut, Elizabeth Sklar, Manuela M. Veloso: RoboCup: Yesterday, Today, and Tomorrow Workshop of the Executive Committee in Blaubeuren, October 2003. RoboCup 2003: 15-34

Ralf Schoknecht, Martin A. Riedmiller: Speeding-up Reinforcement Learning with Multi-step Actions. ICANN 2002: 813-818

Artur Merke, Martin A. Riedmiller: Karlsruhe Brainstormers - A Reinforcement Learning Approach to Robotic Soccer. RoboCup 2001: 435-440

Martin A. Riedmiller, Andrew W. Moore, Jeff G. Schneider: Reinforcement Learning for Cooperating and Communicating Reactive Agents in Electrical Power Grids. Balancing Reactivity and Social Deliberation in Multi-Agent Systems 2000: 137-149

Martin Lauer, Martin A. Riedmiller: An Algorithm for Distributed Reinforcement Learning in Cooperative Multi-Agent Systems. ICML 2000: 535-542

Sebastian Buck, Martin A. Riedmiller: Learning Situation Dependent Success Rates of Actions in a RoboCup Scenario. PRICAI 2000: 809

Martin A. Riedmiller, Artur Merke, David Meier, Andreas Hoffmann, Alex Sinner, Ortwin Thate, R. Ehrmann: Karlsruhe Brainstormers - A Reinforcement Learning Approach to Robotic Soccer. RoboCup 2000: 367-372

Martin A. Riedmiller, Artur Merke, David Meier, Andreas Hoffmann, Alex Sinner, Ortwin Thate: Karlsruhe Brainstormers 2000 Team Description. RoboCup 2000: 485-488

Martin Riedmiller: Concepts and Facilities of a Neural Reinforcement Learning Control Architecture for Technical Process Control. Neural Computing and Applications 8(4): 323-338 (1999)

Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore, Martin A. Riedmiller: Distributed Value Functions. ICML 1999: 371-378

Simone C. Riedmiller, Martin A. Riedmiller: A Neural Reinforcement Learning Approach to Learn Local Dispatching Policies in Production Scheduling. IJCAI 1999: 764-771

Martin A. Riedmiller, Sebastian Buck, Artur Merke, R. Ehrmann, Ortwin Thate, S. Dilger, Alex Sinner, Andreas Hoffmann, Lutz Frommberger: Karlsruhe Brainstormers - Design Principles. RoboCup 1999: 588-591

Karoly Santa, Michael Mews, Martin Riedmiller: A Neural Approach for the Control of Piezoelectric Micromanipulation Robots. Journal of Intelligent and Robotic Systems 22(3-4): 351-374 (1998)

Martin A. Riedmiller: Application of a self-learning controller with continuous control signals based on the DOE-approach. ESANN 1997

Achim Stahlberger, Martin Riedmiller: Fast Network Pruning and Feature Extraction by using the Unit-OBS Algorithm. NIPS 1996: 655-661