Sascha Lange

Sascha Lange, Thomas Gabel and Martin Riedmiller. Batch Reinforcement Learning. In Wiering, M. and van Otterlo, M., editors, Reinforcement Learning: State-of-the-Art, Springer, 2012. Amazon

Martin Lauer, Miriam Schönbein, Sascha Lange and Stefan Welker. 3D-objecttracking with a mixed omnidirectional stereo camera system. Mechatronics 21(2), pp. 390-398, 2011.

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

Martin Riedmiller, Thomas Gabel, Roland Hafner, Sascha Lange, Reinforcement Learning for Robot Soccer. Autonomous Robots 27(1): pp. 55-73, 2009.

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

Tim C. Kietzmann, Sascha Lange, Martin Riedmiller, Incremental GRLVQ: Learning Relevant Features for 3D Object Recognition. Neurocomputing 71(13-15): pp. 2868-2879, 2008.

Martin Lauer, Sascha Lange, Martin Riedmiller, Motion Estimation of Moving Objects for Autonomous Mobile Robots. Künstliche Intelligenz, 1/2006, pp. 11-17, 2005.

João Alves, Sascha Lange, and Martin Riedmiller. Case Study: Behavioral Prediction of Future Revenues in Freemium Games. NC2 Workshop, 36th German Conference on Pattern Recognition (GCPR 2014), 2014.

João Alves, José Neves, Sascha Lange, Martin Riedmiller. Knowledge Extraction from the Behaviour of Players in a Web Browser Game. Proc. of 8th International Conference on Knowledge, Information and Creativity Support Systems (KICSS 2013). 2013.

Martin Riedmiller, Sascha Lange and Arne Voigtländer. Autonomous reinforcement learning on raw visual input data in a real world application. International Joint Conference on Neural Networks (IJCNN 2012). Brisbane, Australia, 2012.

Jan Mattner, Sascha Lange, Martin Riedmiller. Learn to Swing Up and Balance a Real Pole Based on Raw Visual Input Data. In Proceedings of the 19th International Conference on Neural Information Processing (5) (ICONIP 2012). pp. 126–133. 2012.

Andreas Witsch, Roland Reichle, Sascha Lange, Martin Riedmiller and Kurt Geihs. Enhancing the Episodic Natural Actor-Critic Algorithm by a Regularisation Term to Stabilize Learning of Control Structures. In Proc. of the IEEE Symposium on Approximate Dynamic Programming and Reinforcement Learning (ADPRL 2011), Paris, 2011.

Sascha Lange, Martin Riedmiller, Deep Auto-Encoder Neural Networks in Reinforcement Learning. In Proc. of the International Joint Conference on Neural Networks (IJCNN 2010), 2010.

Sascha Lange, Martin Riedmiller, Deep Learning of Visual Control Policies. In Proc. of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2010), 2010.

Sascha Lange, Martin Riedmiller, A Vision for Reinforcement Learning and its Implications for Neural Computation. NC2 Workshop, German Conference on Artificial Intelligence (KI2010), Karlsruhe, Germany, 2010.

Martin Riedmiller, Roland Hafner, Sascha Lange, Martin Lauer, Learning to dribble on a real robot by success and failure. In Proc. of the IEEE International Conference on Robotics and Automation (ICRA 2008), pp 2207-2208, 2007.

Arne Voigtländer, Sascha Lange, Martin Lauer, Martin Riedmiller, Real-time 3D Ball Recognition using Perspective and Catadioptric Cameras. In Proc. of the 3rd European Conference on Mobile Robots (ECMR), 2007.

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

Thomas Gabel, Roland Hafner, Sascha Lange, Martin Lauer, Martin Riedmiller, Bridging the Gap: Learning in the RoboCup Simulation and Midsize League. In Proc. of the 7th Portuguese Conference on Automatic Control (Controlo 2006), 2006.

Sascha Lange, Martin Riedmiller. Appearance Based Robot Discrimination using Eigenimages. In RoboCup 2006: Robot Soccer World Cup X, LNCS, Springer, 2006.

Martin Lauer, Sascha Lange, Martin Riedmiller. Modeling Moving Objects in a Dynamically Changing Robot Application. In Ulrich Furbach (ed.), KI 2005: Advances in Artificial Intelligence, pp. 291-303, Springer, 2005.

Martin Lauer, Sascha Lange, Martin Riedmiller, Calculating the perfect match: An efficient and accurate approach for robot self-localisation. In A. Bredenfeld, A. Jacoff, I. Noda and Y. Takahashi, (editors), RoboCup 2005: Robot Soccer World Cup IX, LNCS. Springer, 2005.

Sascha Lange, Martin Riedmiller. Evolution of Computer Vision Subsystems in Robot Navigation and Image Classification Tasks. In: D. Nardi, M. Riedmiller, C. Sammut and J. Santos-Victor (editors), RoboCup-2004: Robot Soccer World Cup VIII, Springer, LNCS, 2005

Sascha Lange, Tiefes Reinforcement Lernen auf Basis visueller Wahrnehmungen. Doctorate thesis, Department of Mathematics / Computer Science, University of Osnabrück, 2010. PDF
Supervisors: Prof. Dr. Martin Riedmiller, Prof. Dr. Barbara Hammer

Sascha Lange, Evolution von Bildverarbeitungsschichten. Master thesis, Institute of Cognitive Science, University of Osnabrück, 2004.
Supervisors: Prof. Dr. Martin Riedmiller, Dr. Barbara Hammer

Sascha Lange, Verfolgung von farblich markierten Objekten in 2 Dimensionen. Bachelor thesis, Institute of Cognitive Science, University of Osnabrück, 2001.
Supervisors: Dr. Martin Riedmiller (Karlsruhe), Prof. Dr. Wolfgang Speerschneider

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

Roland Hafner, Sascha Lange, Martin Lauer, Martin Riedmiller, Brainstormers Tribots Team Description. In G. Lakemeyer, E. Sklar, D. Sorrenti, T. Takahashi (editors), RoboCup 2006: Robot Soccer World Cup X, LNCS. Springer, 2006.