Jan Hendrik Metzen's Publications

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Classified by Research Category

• Reinforcement Learning • Brain Computer Interface • Neuroevolution • Graph Matching • Unspecified •

Reinforcement Learning

• Jan Hendrik Metzen. Online Skill Discovery using Graph-based Clustering. Journal of Machine Learning Research, W&CP 24:77–88, 2012.
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• Jan Hendrik Metzen. Online Skill Discovery using Graph-based Clustering. In 10th European Workshop on Reinforcement Learning, (EWRL 2012), pp. , June 2012.
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• Jan Hendrik Metzen. Model-based Evolutionary Policy Search for Skill Learning in Continuous Domains. In 10th European Workshop on Reinforcement Learning, (EWRL 2012), pp. , June 2012.
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• Jan Hendrik Metzen and Frank Kirchner. Model-based direct policy search. In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems, pp. 1589–1590, AAMAS '10, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 2010.
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• Jan Hendrik Metzen, Elsa Andrea Kirchner, Larbi Abdenebaoui, and Frank Kirchner. Learning to Play the BRIO Labyrinth Game. Zeitschrift für Künstliche Intelligenz, Themenheft Reinforcement Learning:34–37, 2009.
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• Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, and Frank Kirchner. Evolving Neural Networks for Online Reinforcement Learning. In Parallel Problem Solving from Nature -- PPSN X, pp. 518–527, September 2008.
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• Jan Hendrik Metzen, Frank Kirchner, Mark Edgington, and Yohannes Kassahun. Towards efficient online reinforcement learning using neuroevolution. In Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation, pp. 1425–1426, GECCO '08, ACM, New York, NY, USA, 2008.
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• Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, and Frank Kirchner. Analysis of an evolutionary reinforcement learning method in a multiagent domain. In Proceedings of the 7th International Conference on Autonomous Agents and Multiagent Systems, pp. 291–298, AAMAS '08, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, May 2008.
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• Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, and Frank Kirchner. Performance Evaluation of EANT in the RoboCup Keepaway Benchmark. In ICMLA '07: Proceedings of the Sixth International Conference on Machine Learning and Applications, pp. 342–347, IEEE Computer Society, Washington, DC, USA, 2007.
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Brain Computer Interface

• David Feess, Mario Michael Krell, and Jan Hendrik Metzen. Comparison of Sensor Selection Mechanisms for an ERP-BasedBrain-Computer Interface. PLOS ONE, , 2013. accepted
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• Jan Hendrik Metzen and Elsa Andrea Kirchner. Rapid Adaptation of Brain Reading Interfaces based on Threshold Adjustment. In Proceedings of the 2011 Conference of the German Classification Society, (GfKl-2011), pp. 138, August 2011.
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• Jan Hendrik Metzen, Su-Kyoung Kim, and Elsa Andrea Kirchner. Minimizing Calibration Time for Brain Reading. In Pattern Recognition, pp. 366–375, Lecture Notes in Computer Science 6835, Springer, August 2011. The original publication is available at www.springerlink.com under http://www.springerlink.com/content/731775n33wg062w2/fulltext.pdf
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• Jan Hendrik Metzen, Su Kyoung Kim, Timo Duchrow, Elsa Andrea Kirchner, and Frank Kirchner. On Transferring Spatial Filters in a Brain Reading Scenario. In Statistical Signal Processing Workshop (SSP), 2011 IEEE, pp. 797–800, June 2011.
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• Sirko Straube, Jan Hendrik Metzen, Anett Seeland, Mario Krell, and Elsa Andrea Kirchner. Choosing an Appropriate Performance Measure: Classification of EEG-Data with Varying Class Distribution. In Proceedings of the 41st Meeting of the Society for Neuroscience 2011, November 2011.
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• Elsa Andrea Kirchner, Hendrik Wöhrle, Constantin Bergatt, Su-Kyoung Kim, Jan Hendrik Metzen, David Feess, and Frank Kirchner. Towards Operator Monitoring via Brain Reading - An EEG-based Approach for Space Applications. In Proceedings of the 10th International Symposium on Artificial Intelligence, Robotics and Automation in Space (iSAIRAS-10), pp. 448–455, September 2010.
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• Elsa Andrea Kirchner, Jan Hendrik Metzen, Timo Duchrow, Su Kyong Kim, and Frank Kirchner. Assisting Telemanipulation Operators via Real-Time Brain Reading. In Lemgoer Schriftenreihe zur industriellen Informationstechnik, Paderborn, September 2009.
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Neuroevolution

• Yohannes Kassahun, Jan Hendrik Metzen, Mark Edgington, and Frank Kirchner. Incremental Acquisition of Neural Structures through Evolution. In Design and Control of Intelligent Robotic Systems, pp. 187–208, 2009.
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• Yohannes Kassahun, Jose de Gea, Mark Edgington, Jan Hendrik Metzen, and Frank Kirchner. Accelerating neuroevolutionary methods using a Kalman filter. In GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation, pp. 1397–1404, ACM, New York, NY, USA, 2008.
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• Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, and Frank Kirchner. Evolving Neural Networks for Online Reinforcement Learning. In Parallel Problem Solving from Nature -- PPSN X, pp. 518–527, September 2008.
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• Jan Hendrik Metzen, Frank Kirchner, Mark Edgington, and Yohannes Kassahun. Towards efficient online reinforcement learning using neuroevolution. In Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation, pp. 1425–1426, GECCO '08, ACM, New York, NY, USA, 2008.
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• Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, and Frank Kirchner. Analysis of an evolutionary reinforcement learning method in a multiagent domain. In Proceedings of the 7th International Conference on Autonomous Agents and Multiagent Systems, pp. 291–298, AAMAS '08, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, May 2008.
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• Yohannes Kassahun, Mark Edgington, Jan H Metzen, Gerald Sommer, and Frank Kirchner. A common genetic encoding for both direct and indirect encodings of networks. In GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation, pp. 1029–1036, ACM, New York, NY, USA, July 2007.
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• Yohannes Kassahun, Jan Metzen, Jose de Gea, Mark Edgington, and Frank Kirchner. A General Framework for Encoding and Evolving Neural Networks. In KI 2007: Advances in Artificial Intelligence, pp. 205–219, Osnabrück, Germany, 2007.
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• Jan Hendrik Metzen, Mark Edgington, Yohannes Kassahun, and Frank Kirchner. Performance Evaluation of EANT in the RoboCup Keepaway Benchmark. In ICMLA '07: Proceedings of the Sixth International Conference on Machine Learning and Applications, pp. 342–347, IEEE Computer Society, Washington, DC, USA, 2007.
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Graph Matching

• Jan Hendrik Metzen, Tim Kröger, Andrea Schenk, Stephan Zidowitz, Heinz-Otto Peitgen, and Xiaoyi Jiang. Matching of anatomical tree structures for registration of medical images. Image and Vision Computing, 27(7):923–933, June 2009.
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• Jan Metzen, Tim Kröger, Andrea Schenk, Stephan Zidowitz, Heinz-Otto Peitgen, and Xiaoyi Jiang. Matching of Tree Structures for Registration of Medical Images. In Graph-Based Representations in Pattern Recognition, pp. 13–24, Springer Verlag, Alicante, Spain, 2007.
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• Jan Hendrik Metzen, Tim Kröger, Andrea Schenk, Stephan Zidowitz, Heinz-Otto Peitgen, and Xiaoyi Jiang. Matching von Baumstrukturen - Zuordnung von Gefäßsystemen aus Leber und Lunge. In Bildverarbeitung für die Medizin 2007, pp. 116–120, March 2007.
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• Jan Hendrik Metzen. Matching von Baumstrukturen in der medizinischen Bildverarbeitung. Master's Thesis, Westfälische Wilhelms-Universität Münster,2006.
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Unspecified

• Constantin Bergatt, Jan Hendrik Metzen, Elsa Andrea Kirchner, and Frank Kirchner. Quantification and Minimization of the Simulation-Reality-Gap on a BRIO Labyrinth Game. In Proceedings of the first International Workshop on Learning and Data Mining for Robotics (LEMIR-09), Bled, Slovenia, 2009.
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• Malte Römmermann, Mark Edgington, Jan Hendrik Metzen, Jose de Gea, Yohannes Kassahun, and Frank Kirchner. Learning Walking Patterns for Kinematically Complex Robots Using Evolution Strategies. In Parallel Problem Solving from Nature -- PPSN X, pp. 1091–1100, 2008.
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• Jens Müller, Jan Hendrik Metzen, Alexander Ploss, Maraike Schellmann, and Sergei Gorlatch. Rokkatan: Scaling an RTS Game Design to the Massively Multiplayer Realm. In ACM SIGHCHI International Conference on Advances in Computer Entertainment Technology (ACE 05), pp. 125–132, ACM, Valencia, Spain, June 2005.
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