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Prof. Wolfgang Ertel
Wolfgang Ertel
Professor Dr. rer. nat.

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[1] Richard Cubek, Wolfgang Ertel, and Günther Palm. High-level learning from demonstration with conceptual spaces and subspace clustering. In Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, Washington, 2015. [ bib ]
[2] V. Zakharov, R. Cubek, and W. Ertel. Transparent integration of a real-time collision safety system to a motor control chain of a service robot. In Proceedings of the 7th Annual International Conference on Technologies for Practical Robot Applications (TEPRA 2015), Boston, Massachusetts, 2015. [ bib ]
[3] W. Ertel, S. Pfiffner, B. Reiner, B. Stähle, M. Schneider, J. Schmal, B. Weber-Fiori, and M. H.-J. Winter. A service robot platform for individuals with disabilities. In Proceedings of the 1. BW-CAR Symposium on Information and Communication Systems (SInCom), Villingen-Schwenningen, Germany, pages 84-88, 2014. [ bib ]
[4] B. Reiner, W. Ertel, H. Posenauer, and M. Schneider. Lat: A simple learning from demonstration method. In IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014, Chicago, 2014. [ bib ]
[5] W. Ertel, R. Lehmann, R. Medow, M. Finkbeiner, and A. Meyer. Model Free Diagnosis of Pneumatic Systems using Machine Learning. In 9th International Fluid Power Conference, pages 340-349, Aachen, 2014. [ bib ]
[6] A. V. Ngo and W. Ertel. Monte carlo tree search for bayesian reinforcement learning. Applied Intelligence, (12), 2012. [ bib ]
[7] S. Schädle and W. Ertel. Dexterous manipulation using hierarchical reinforcement learning. In Autonomous Learning workshop, IEEE International Conference on Robotics and Automation (ICRA) 2013, Karlsruhe, Germany, 2013. http://autonomous-learning.org/wp-publications/schaedle2013. [ bib ]
[8] A. V. Ngo, W. Ertel, V.-H. Dung, and T.C. Chung. Monte carlo tree search for bayesian reinforcement learning. In 11th International Conference on Machine Learning and Applications (ICMLA 2012) December 12-15, Boca Raton, Florida, USA, 2012. [ bib ]
[9] A. V. Ngo and W. Ertel. Reinforcement learning combined with human feedback in continuous state and action spaces. In IEEE Conference on Development and Learning / EpiRob 2012 (ICDL-EpiRob), San Diego, USA, 2012. [ bib ]
[10] A. V. Ngo and W. Ertel. Learning via human feedback in continuous state and action spaces. In 2012 AAAI Fall Symposium Series, Robots Learning Interactively from Human Teachers, (RLIHT), Arlington, Virginia, USA, 2012. [ bib ]
[11] T. Fromm, B. Stähle, and W. Ertel. Robust multi-algorithm object recognition using machine learning methods. In IEEE International Conference on Multisensor Fusion and Information Integration, Hamburg, Germany, 2012. [ bib ]
[12] M. Bertsche, T. Fromm, and W. Ertel. BOR3D: A Use-Case-Oriented Software Framework for 3-D Object Recognition. In IEEE Conference on Technologies for Practical Robot Applications (TePRA), 2012. [ bib ]
[13] R. Cubek and W. Ertel. Conceptual similarity as a key to high-level robot programming by demonstration. In ROBOTIK 2012, 7th German Conference on Robotics, Munich, Germany, 2012. [ bib ]
[14] R. Cubek and W. Ertel. Learning and Execution of High-Level Concepts with Conceptual Spaces and PDDL. In 3rd Workshop on Learning and Planning, ICAPS (21st International Conference on Automated Planning and Scheduling), Freiburg, Germany, 2011. [ bib ]
[15] W. Ertel, L. Jans, W. Herzhauser, and J. Feßler. An Enigma Replica and its Blueprints. Cryptologia, 35(1):16-21, 2011. http://www.tandfonline.com/doi/abs/10.1080/01611194.2010.533256. [ bib ]
[16] M. Tokic, A. Usadel, J. Fessler, and W. Ertel. On an educational approach of biologically-motivated robot learning. In Proc. 1st International Conference on Robotics in Education, Bratislava, Slovakia, 2010. [ bib ]
[17] H. Voos, H. Bou Ammar, and W. Ertel. Controller Design for Quadrotor UAV's using Reinforcement Learning. In Proc. IEEE Multi-Conference on Systems and Control, Yokohama, Japan, 2010. [ bib ]
[18] M. Schneider and W. Ertel. Robot Learning by Demonstration with Local Gaussian Process Regression. In Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), Taipeh, Taiwan, 2010. [ bib ]
[19] M. Schneider, R. Cubek, T. Fromm, and W. Ertel. Combining gaussian processes and conventional path planning in a learning from demonstration framework. In Proceedings of the Eurobot Conference 2010, Rapperswil-Jona (CH), 2010. [ bib ]
[20] W. Ertel, M. Schneider, R. Cubek, and M. Tokic. The Teaching-Box: A universal robot learning framework. In Proceedings of the 14th International Conference on Advanced Robotics (ICAR 2009), Munich, 2009. www.servicerobotik.hs-weingarten.de/teachingbox. [ bib ]
[21] M. Tokic, W. Ertel, and J. Fessler. The crawler, a class room demonstrator for reinforcement learning. In Proceedings of the 22nd International Florida Artificial Intelligence Research Society Conference (FLAIRS 09), Menlo Park, California, 2009. AAAI Press. [ bib ]
[22] Ch. Folkers and W. Ertel. High performance realtime vision for mobile robots on the gpu. In International Workshop on Robot Vision, 2nd International Conference on Computer Vision Theory and Applications (VISAPP), Barcelona, 2007. [ bib ]
[23] M. Tokic, W. Ertel, and H.-P. Radtke. Reinforcement learning on a simple real walking robot. In KI 2006, 29th annual German Conference on Artificial Intelligence, June 2006. [ bib ]
[24] W. Ertel, J. Fessler, and N. Hochgeschwender. Flexible combination of vision, control and drive in autonomous mobile robots. In 19. Fachgespräch Autonome Mobile Systeme AMS 2005, Informatik-Aktuell, Stuttgart, 2005. Springer-Verlag. www.springerlink.com/content/r1m73w7042936t86/?p=9fc23082baae484bb73f4c09aa523e09&pi=0. [ bib ]
[25] W. Ertel, J. Fessler, and N. Hochgeschwender. A universal modular autonomous robot architecture. In J. Filipe, J. Cetto, and J. Ferrier, editors, Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics, volume III, pages 391-394, 2005. [ bib ]
[26] E. Schreck and W. Ertel. Disk drive generates high speed real random numbers. Microsystem Technologies, 11(8-10):616-622, 2005. http://dx.doi.org/10.1007/s00542-005-0532-6. [ bib ]
[27] E. Schreck and W. Ertel. Disk drive generates high speed real random numbers. In JSME-IIP/ASME-ISPS Joint Conference on Micromechatronics for Information and Precision Equipment (IIP/ISPS Joint MIPEB!G03), 2003. [ bib ]
[28] M. Schramm, W. Ertel, and W. Rampf. Diagnosesystem für Blinddarmentzündung. PraxisComputer, September 2001. [ bib ]
[29] M. Schramm, W. Ertel, and W. Rampf. Bestimmung der Wahrscheinlichkeit einer Appendizitis mit LEXMED. Biomedical Journal, 57:9-11, April 2001. [ bib ]
[30] W. Ertel and M. Schramm. Combining Expert Knowledge and Data via Probabilistic Rules with an Application to Medical Diagnosis. In UAI-2000 Workshop on Fusion of Domain Knowledge with Data for Decision Support, Stanford CA, 2000. [ bib ]
[31] W. Ertel and M. Schramm. Combining Data and Knowledge by MaxEnt-Optimization of Probability Distributions. In PKDD'99 (3rd European Conference on Principles and Practice of Knowledge Discovery in Databases), volume 1704 of LNCS, pages 323-328, Prague, 1999. Springer Verlag. http://www.springerlink.com/content/5pvrgvjuxr7jnuea/. [ bib ]
[32] M. Schramm and W. Ertel. Reasoning with Probabilities and Maximum Entropy: The System PIT and its Application in LEXMED. In K. Inderfurth et al, editor, Operations Research Proceeedings (SOR'99), pages 274-280. Springer Verlag, 2000. [ bib ]
[33] J. Aczél and W. Ertel. A new formula for speedup and its characterization. Acta Informatica, 34:637-652, 1997. [ bib ]
[34] W. Ertel. Characterization of an alternative speedup function (in: Report of the 33. intl. sympos. on functional equations). Aequationes Mathematicae, 49:166-202, 1995. [ bib ]
[35] W. Ertel. On the Definition of Speedup. In PARLE'94, Parallel Architectures and Languages Europe, pages 289-300. LNCS 817, Springer Verlag, 1994. [ bib ]
[36] M. Luby and W. Ertel. Optimal Parallelisation of Las Vegas Algorithms. In STACS'94, Symposium on Theoretical Aspects of Computer Science, pages 463-475. LNCS 775, Springer Verlag, 1994. [ bib ]
[37] W. Ertel. Massively parallel search with random competition. In Working Notes, AAAI Spring Symposium: Innovative Applications of Massive Parallelism, Stanford Univ., 1993. [ bib ]
[38] W. Ertel. Parallele Suche mit randomisiertem Wettbewerb in Inferenzsystemen, volume 25 of DISKI. Infix-Verlag, St. Augustin, 1993. Dissertation, Technische Universität München. [ bib ]
[39] E. Jessen, W. Ertel, and C. Suttner. Optimal Multiprogramming Control for Parallel Computations. In A. Bode and M. Dal Cin, editors, Parallel Computer Architectures: Theory, Hardware, Software, Applications, pages 49-65. Springer LNCS 732, 1993. [ bib ]
[40] W. Ertel. OR-Parallel Theorem Proving with Random Competition. In A. Voronkov, editor, LPAR'92: Logic Programming and Automated Reasoning, pages 226-237, St.Petersburg, Russia, July 1992. LNAI 624, Springer Verlag. [ bib ]
[41] W. Ertel. Performance of Competitive OR-Parallelism. In Parallel Execution of Logic Programs (ICLP'91 Pre-conference Workshop), pages 132-145, Paris, 1991. LNCS 569, Springer-Verlag. [ bib ]
[42] W. Ertel and Ch. Suttner. Project paris: Parallelisation of inference systems. In International Workshop on Parallelization in Inference Systems, volume 590 of Lecture Notes In Computer Science, page 363. Springer, London, 1990. [ bib ]
[43] W. Ertel. Random Competition: A Simple, but Efficient Method for Parallelizing Inference Systems. In Parallelization in Inference Systems, pages 195-209, Berlin/New York, 1992. LNAI 590, Springer-Verlag. [ bib ]
[44] Ch. Suttner and W. Ertel. Using Back-Propagation Networks for Guiding the Search of a Theorem Prover. Int. J. of Neural Networks Research & Applications, 2(1):3-16, 1991. [ bib ]
[45] Ch. Suttner and W. Ertel. Automatic Acquisition of Search Guiding Heuristics. In 10th Int. Conf. on Automated Deduction, pages 470-484. Springer-Verlag, LNAI 449, 1990. [ bib ]
[46] W. Ertel, J. Schumann, and Ch. Suttner. Learning Heuristics for a Theorem Prover using Back Propagation. In J. Retti and K. Leidlmair, editors, 5. Österreichische Artificial-Intelligence-Tagung, pages 87-95. Informatik-Fachberichte 208, Springer-Verlag, Berlin, Heidelberg, 1989. [ bib ]
[47] W. Ertel, F. Kurfeß, X. Pandolfi, and J. Schumann. PARTHEO, A Parallel Inference Machine. In PARLE, Parallel Architectures and Languages Europe, volume 365 of Lecture Notes In Computer Science, pages 458-476. Springer Verlag, Berlin, 1989. [ bib ]
[48] F. Kurfeß, X. Pandolfi, Z. Belmesk, W. Ertel, R. Letz, and J. Schumann. PARTHEO and FP2: Design of a Parallel Inference Machine. In Ph. Treleaven, editor, Parallel Computers: Object-Oriented, Functional, Logic, chapter 9, pages 259-297. Wiley & Sons, Chichester, 1989. [ bib ]
[49] W. Ertel, K. Froböse, and J. Jäckle. Constrained diffusion dynamics in the hard-square lattice gas at high density. The Journal of Chemical Physics, 88(8):5027-5034, 1988. [ bib | DOI | http ]

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