Please note: This is a beta version of the new dblp website.
You can find the classic dblp view of this page here.
You can find the classic dblp view of this page here.
Martin A. Riedmiller
Martin Riedmiller
2010 – today
- 2012
[c55]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- [c54]Jost Tobias Springenberg, Martin Riedmiller: Learning Temporal Coherent Features through Life-Time Sparsity. ICONIP (1) 2012: 347-356
- [c53]Manuel Blum, Jost Tobias Springenberg, Jan Wülfing, Martin Riedmiller: A learned feature descriptor for object recognition in RGB-D data. ICRA 2012: 1298-1303
- [c52]Sascha Lange, Martin Riedmiller, Arne Voigtländer: Autonomous reinforcement learning on raw visual input data in a real world application. IJCNN 2012: 1-8
- [c51]Oliver Obst, Martin Riedmiller: Taming the reservoir: Feedforward training for recurrent neural networks. IJCNN 2012: 1-7
- [c50]Jan Wülfing, Martin Riedmiller: Unsupervised Learning of Local Features for Music Classification. ISMIR 2012: 139-144
- 2011
- [j13]Roland Hafner, Martin Riedmiller: Reinforcement learning in feedback control - Challenges and benchmarks from technical process control. Machine Learning 84(1-2): 137-169 (2011)
- 2010
- [j12]Martin Lauer, Roland Hafner, Sascha Lange, Martin Riedmiller: Cognitive concepts in autonomous soccer playing robots. Cognitive Systems Research 11(3): 287-309 (2010)
- [c49]
- [c48]Sascha Lange, Martin Riedmiller: Deep auto-encoder neural networks in reinforcement learning. IJCNN 2010: 1-8
- [c47]Thomas Gabel, Martin Riedmiller: On Progress in RoboCup: The Simulation League Showcase. RobuCup 2010: 36-47
2000 – 2009
- 2009
- [j11]Martin Riedmiller, Thomas Gabel, Roland Hafner, Sascha Lange: Reinforcement learning for robot soccer. Auton. Robots 27(1): 55-73 (2009)
- [j10]Tim C. Kietzmann, Sascha Lange, Martin A. Riedmiller: Computational object recognition: a biologically motivated approach. Biological Cybernetics 100(1): 59-79 (2009)
- [c46]Tim C. Kietzmann, Martin Riedmiller: The Neuro Slot Car Racer: Reinforcement Learning in a Real World Setting. ICMLA 2009: 311-316
- 2008
- [c45]Thomas Gabel, Martin A. Riedmiller: Reinforcement learning for DEC-MDPs with changing action sets and partially ordered dependencies. AAMAS (3) 2008: 1333-1336
- [c44]Thomas Gabel, Martin Riedmiller: Increasing Precision of Credible Case-Based Inference. ECCBR 2008: 225-239
- [c43]Thomas Gabel, Martin Riedmiller: Evaluation of Batch-Mode Reinforcement Learning Methods for Solving DEC-MDPs with Changing Action Sets. EWRL 2008: 82-95
- [c42]Martin A. Riedmiller, Roland Hafner, Sascha Lange, Martin Lauer: Learning to dribble on a real robot by success and failure. ICRA 2008: 2207-2208
- [c41]Thomas Gabel, Martin A. Riedmiller: Joint Equilibrium Policy Search for Multi-Agent Scheduling Problems. MATES 2008: 61-72
- [c40]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
- 2007
- [c39]Martin A. Riedmiller, Thomas Gabel: On Experiences in a Complex and Competitive Gaming Domain: Reinforcement Learning Meets RoboCup. CIG 2007: 17-23
- [c38]
- [c37]Arne Voigtländer, Sascha Lange, Martin Lauer, Martin A. Riedmiller: Real-time 3D Ball Recognition using Perspective and Catadioptric Cameras. EMCR 2007
- [c36]Verena Heidrich-Meisner, Martin Lauer, Christian Igel, Martin A. Riedmiller: Reinforcement learning in a nutshell. ESANN 2007: 277-288
- [c35]Martin Riedmiller, Michael Montemerlo, Hendrik Dahlkamp: Learning to Drive a Real Car in 20 Minutes. FBIT 2007: 645-650
- [c34]Thomas Gabel, Martin Riedmiller: An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs. ICCBR 2007: 344-358
- [c33]Roland Hafner, Martin Riedmiller: Neural Reinforcement Learning Controllers for a Real Robot Application. ICRA 2007: 2098-2103
- [c32]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
- 2006
- [j9]Martin A. Riedmiller, Thomas Gabel, Roland Hafner, Sascha Lange, Martin Lauer: Die Brainstormers: Entwurfsprinzipien lernfähiger autonomer Roboter. Informatik Spektrum 29(3): 175-190 (2006)
- [j8]Thomas Gabel, Martin A. Riedmiller: Learning a Partial Behavior for a Competitive Robotic Soccer Agent. KI 20(2): 18-23 (2006)
- [c31]Thomas Gabel, Martin Riedmiller: Reducing policy degradation in neuro-dynamic programming. ESANN 2006: 653-658
- [c30]Thomas Gabel, Martin Riedmiller: Multi-agent Case-Based Reasoning for Cooperative Reinforcement Learners. ECCBR 2006: 32-46
- [c29]Sascha Lange, Martin Riedmiller: Appearance-Based Robot Discrimination Using Eigenimages. RoboCup 2006: 499-506
- 2005
- [j7]Martin A. Riedmiller, Daniel Withopf: Effective Methods for Reinforcement Learning in Large Multi-Agent Domains. it - Information Technology 47(5): 241-249 (2005)
- [c28]Martin Riedmiller: Neural Fitted Q Iteration - First Experiences with a Data Efficient Neural Reinforcement Learning Method. ECML 2005: 317-328
- [c27]Thomas Gabel, Martin A. Riedmiller: CBR for State Value Function Approximation in Reinforcement Learning. ICCBR 2005: 206-221
- [c26]Martin Lauer, Sascha Lange, Martin A. Riedmiller: Modeling Moving Objects in a Dynamically Changing Robot Application. KI 2005: 291-303
- [c25]Alexander Sung, Artur Merke, Martin A. Riedmiller: Reinforcement Learning Using a Grid Based Function Approximator. Biomimetic Neural Learning for Intelligent Robots 2005: 235-244
- [c24]Martin Lauer, Sascha Lange, Martin Riedmiller: Calculating the Perfect Match: An Efficient and Accurate Approach for Robot Self-localization. RoboCup 2005: 142-153
- [c23]
- [c22]Martin Riedmiller, Daniel Withopf: Comparing different methods to speed up reinforcement learning in a complex domain. SMC 2005: 3185-3190
- [c21]Martin Riedmiller: Neural reinforcement learning to swing-up and balance a real pole. SMC 2005: 3191-3196
- [e1]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
- 2004
- [j6]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)
- [j5]Martin Riedmiller, François Fages, Malik Ghallab, Wolfgang Wahlster, Jörg H. Siekmann: Invited talks. KI 18(3): 44- (2004)
- [j4]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)
- [c20]Martin Lauer, Martin Riedmiller: Reinforcement Learning for Stochastic Cooperative Multi-Agent Systems. AAMAS 2004: 1516-1517
- [c19]
- [c18]Sascha Lange, Martin Riedmiller: Evolution of Computer Vision Subsystems in Robot Navigation and Image Classification Tasks. RobuCup 2004: 184-195
- 2003
- [j3]Ralf Schoknecht, Martin Riedmiller: Reinforcement learning on explicitly specified time scales. Neural Computing and Applications 12(2): 61-80 (2003)
- [c17]Ralf Schoknecht, Martin A. Riedmiller: Learning to Control at Multiple Time Scales. ICANN 2003: 479-487
- [c16]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
- [c15]Roland Hafner, Martin Riedmiller: Reinforcement learning on an omnidirectional mobile robot. IROS 2003: 418-423
- [c14]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
- [c13]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
- 2002
- [c12]Ralf Schoknecht, Martin A. Riedmiller: Speeding-up Reinforcement Learning with Multi-step Actions. ICANN 2002: 813-818
- 2001
- [c11]Artur Merke, Martin A. Riedmiller: Karlsruhe Brainstormers - A Reinforcement Learning Approach to Robotic Soccer. RoboCup 2001: 435-440
- 2000
- [c10]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
- [c9]Martin Lauer, Martin A. Riedmiller: An Algorithm for Distributed Reinforcement Learning in Cooperative Multi-Agent Systems. ICML 2000: 535-542
- [c8]Sebastian Buck, Martin A. Riedmiller: Learning Situation Dependent Success Rates of Actions in a RoboCup Scenario. PRICAI 2000: 809
- [c7]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
- [c6]Martin A. Riedmiller, Artur Merke, David Meier, Andreas Hoffmann, Alex Sinner, Ortwin Thate: Karlsruhe Brainstormers 2000 Team Description. RoboCup 2000: 485-488
1990 – 1999
- 1999
- [j2]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)
- [c5]Jeff G. Schneider, Weng-Keen Wong, Andrew W. Moore, Martin A. Riedmiller: Distributed Value Functions. ICML 1999: 371-378
- [c4]Simone C. Riedmiller, Martin A. Riedmiller: A Neural Reinforcement Learning Approach to Learn Local Dispatching Policies in Production Scheduling. IJCAI 1999: 764-771
- [c3]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
- 1998
- [j1]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)
- 1997
- [c2]Martin A. Riedmiller: Application of a self-learning controller with continuous control signals based on the DOE-approach. ESANN 1997
- 1996
- [c1]Achim Stahlberger, Martin Riedmiller: Fast Network Pruning and Feature Extraction by using the Unit-OBS Algorithm. NIPS 1996: 655-661
Coauthor Index
data released under the ODC-BY 1.0 license. See also our legal information page
last updated on 2013-04-11 03:36 CEST by the dblp team