Ruhr-Universität Bochum [Ruhr-Universität Bochum]
[INI] [INI]

Structure Optimization and Neural Networks
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Chairs
• Prof. Dr. Laurenz Wiskott
• Prof. Dr. Gregor Schöner

Research groups
• Theory of embodied cognition
Prof. Dr. Gregor Schöner
• Theory of Neural Systems
Prof. Dr. Laurenz Wiskott
• Neural Plasticity Lab
PD Dr. Hubert Dinse
• Real-Time Optical Imaging Lab
Dr. Dirk Jancke
• Organic Computing
Dr. Rolf Würtz
• Optimization of adaptive systems
Jun.-Prof. Dr. Christian Igel
• Autonomous robotics
Dr. Ioannis Iossifidis
• Medical Image Processing
Dr. Susanne Winter
• Real-time computer vision
Jan Salmen
• Multi-sensory fusion
Dr. Andrey Bogdanov

Publications of the SONN group

The following list contains all publications of the SONN group sorted by the name of first author and by date. Recent publications are on top of the list; scroll down for older ones. For most of the publications a downloadable (gzipped) postscript or PDF version is available.

[gepperth:05] Gepperth, A. and S. Roth (2005). Applications of multi-objective structure optimization. In 13th European Symposium on Artificial Neural Networks (ESANN 2005). Evere, Belgium: d-side publications. submitted.
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[chalimourda:04] Chalimourda, A., B. Schölkopf, and A. J. Smola (2004). Experimentally optimal nu in support vector regression for different noise models and parameter settings. Neural Networks 17(1), 127-141.
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[toussaint:04] Toussaint, M. (2004). Learning a world model and planning with a self-organizing, dynamic neural system. In Advances in Neural Information Processing Systems 16 (NIPS 2003), pp. 929-936. MIT Press, Cambridge.
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[wiegand:04] Wiegand, S., C. Igel, and U. Handmann (2004). Evolutionary optimization of neural networks for face detection. In 12th European Symposium on Artificial Neural Networks (ESANN 2004), pp. 139-144. Evere, Belgium: d-side publications.
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[wiegand:04b] Wiegand, S., C. Igel, and U. Handmann (2004). Evolutionary multi-objective optimisation of neural networks for face detection. International Journal of Computational Intelligence and Applications 4(3), 237-253.
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[jin:03] Jin, Y. C., M. Hüsken, and B. Sendhoff (2003, July). Quality measures for approximate models in evolutionary computation. In Proceedings of 2003 GECCO Workshop on Learning, Adaptation and Approximation in Evolutionary Computation, Chicago. To appear.
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[toussaint:03d] Toussaint, M. (2003, April). The evolution of genetic representations and modular neural adaptation. PhD thesis, Institut für Neuroinformatik, Ruhr-Universiät-Bochum, Germany. Published with thee Logos Verlag Berlin (2004), ISBN 3-8325-0579-2,173 pages.
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[buecher:03] Bücher, T., C. Curio, H. Edelbrunner, C. Igel, D. Kastrup, I. Leefken, G. Lorenz, A. Steinhage, and W. von Seelen (2003). Image processing and behaviour planning for intelligent vehicles. IEEE Transactions on Industrial Electronics 50(1).
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[huesken:03] Hüsken, M. and P. Stagge (2003). Recurrent neural networks for time series classification. Neurocomputing 50(C), 223-235.
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[huesken:03b] Hüsken, M., Y. C. Jin, and B. Sendhoff (2003). Structure Optimization of Neural Networks for Evolutionary Design Optimization. Soft Computing. Special Issue on Approximation and Learning in Evolutionary Computation. In press.
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[igel:02b] Igel, C. and M. Hüsken (2003). Empirical evaluation of the improved Rprop learning algorithm. Neurocomputing 50(C), 105-123.
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[igel:03] Igel, C. and M. Toussaint (2003). On classes of functions for which no free lunch results hold. Information Processing Letters. Accepted.
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[toussaint:03] Toussaint, M. (2003). On the evolution of phenotypic exploration distributions. In C. Cotta, K. De Jong, R. Poli, and J. Rowe (Eds.), Foundations of Genetic Algorithms 7 (FOGA VII), pp. 169-182. Morgan Kaufmann. In Press.
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[toussaint:03b] Toussaint, M. (2003). The structure of evolutionary exploration: On crossover, buildings blocks, and Estimation-Of-Distribution algorithms. In 2003 Genetic and Evolutionary Computation Conference (GECCO 2003), pp. 1444-1456.
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[toussaint:03c] Toussaint, M. (2003). Demonstrating the evolution of complex genetic representations: An evolution of artificial plants. In 2003 Genetic and Evolutionary Computation Conference (GECCO 2003), pp. 86-97.
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[wiebringhaus:03] Wiebringhaus, T., U. Faigle, D. Schomburg, J. Gebert, C. Igel, and G.-W. Weber (2003). Protein fold class prediction using neural networks reconsidered. In Currents in Computational Molecular Biology, The Seventh Annual International Conference on Research in Computational Molecular Biology (RECOMB 2003), pp. 225-226.
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[huesken:02b] Hüsken, M., C. Igel, and M. Toussaint (2002, September). Task-dependent evolution of modularity in neural networks. Connection Science 14(3), 219-229.
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[dinse:02] Dinse, H. R., M. Hüsken, C. Igel, C. Klaes, M. Nunkesser, S. Schneider, and J. Wiemer (2002). Derandomized evolution strategies in computational neuroscience. In W. Banzhaf and J. A. Foster (Eds.), Biological Applications of Genetic and Evolutionary Computation (BioGEC 2002) - A Bird-of-a-feather Workshop at the Genetic and Evolutionary Computation Conference (GECCO 2002).
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[huesken:02] Hüsken, M. and C. Igel (2002, 9-13 July). Balancing learning and evolution. In W. B. Langdon, E. Cantú-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A. C. Schultz, J. F. Miller, E. Burke, and N. Jonoska (Eds.), GECCO-2002: Proceedings of the Generic and Evolutionary Computation Conference, San Francisco, CA 94104, USA, pp. 391-398. Morgan Kaufmann Publishers.
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[huesken:02c] Hüsken, M., Y. Jin, and B. Sendhoff (2002, 8 July). Structure optimization of neural networks for evolutionary design optimization. In A. M. Barry (Ed.), GECCO 2002: Proceedings of the Bird of a Feather Workshops, Genetic and Evolutionary Computation Conference, 445 Burgess Drive, Menlo Park, CA 94025, pp. 13-16. AAAI, Menlo Park, CA, USA.
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[igel:02a] Igel, C. and P. Stagge (2002). Effects of phenotypic redundancy in structure optimization. IEEE Transactions on Evolutionary Computation 6(1), 74-85.
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[igel:02c] Igel, C., W. von Seelen, W. Erlhagen, and D. Jancke (2002). Evolving field models for inhibition effects in early vision. Neurocomputing 44-46(C), 467-472. Will also appear in J. M. Bower (Edt.): Computational Neuroscience: Trends in Research 2001, Elsevier Science. In Press.
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[igel:02d] Igel, C. and M. Kreutz (2002). Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. Neurocomputing. In Press.
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[igel:02e] Igel, C. and P. Stagge (2002). Graph isomorphisms effect structure optimization of neural networks. In International Joint Conference on Neural Networks 2002 (IJCNN), pp. 142-147. IEEE Press.
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Keywords: evolutionary structure optimization, graph isomorphism, graph database, redundancy
[toussaint:02] Toussaint, M. (2002). On model selection and the disability of neural networks to decompose tasks. In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2002), pp. 245-250.
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[toussaint:02b] Toussaint, M. (2002). A neural model for multi-expert architectures. In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2002), pp. 2755-2760.
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[toussaint:02c] Toussaint, M. and C. Igel (2002). Neutrality: A necessity for self-adaptation. In Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2002), pp. 1354-1359.
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[weinert:02] Weinert, K., O. Webber, M. Hüsken, J. Mehnen, and W. Theis (2002). Analysis and prediction of dynamic disturbances of the BTA deep hole drilling process. In Proceedings of the 3rd CIRP International Seminar on Intelligent Computation in Manufacturing Engineering (ICME 2002).
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[toussaint:01a] Toussaint, M. (2001, May). Self-adaptive exploration in evolutionary search. Internal Report IRINI 01-05, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany. Los Alamos e-Print Archive (http://arXiv.org/abs/physics/0102009).
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[bergener:01] Bergener, T., C. Bruckhoff, and C. Igel (2001). Parameter optimization for visual obstacle detection using a derandomized evolution strategy. In J. Blanc-Talon and D. Popesc (Eds.), Imaging and Vision Systems: Theory, Assessment and Applications, Volume 9 of Advances in Computation: Theory and Practice, Chapter 13, pp. 265-279. Huntington, NY 11743 (USA): NOVA Science Books.
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[busse:01] Busse, A., M. Hüsken, and P. Stagge (2001). Offline-Analyse eines BTA-Tiefbohrprozesses. Technical Report 16/01, SFB 475, Fachbereich Statistik, Universität Dortmund, 44221 Dortmund, Deutschland.
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[edelbrunner:01] Edelbrunner, H., U. Handmann, C. Igel, I. Leefken, and W. von Seelen (2001). Application and optimization of neural field dynamics for driver assistance. In The IEEE 4th International Conference on Intelligent Transportation Systems (ITSC '01), Piscataway, NJ, pp. 309-314. IEEE Press.
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Keywords: driver assistance, evolutionary optimization, evolution strategy, neural field
[huesken:01b] Hüsken, M., C. Igel, and M. Toussaint (2001). Task-dependent evolution of modularity in neural networks - a quantitative case study. In E. D. Goodman (Ed.), 2001 Genetic and Evolutionary Computation Conference (GECCO 2001) - Late-Breaking Papers, pp. 187-193.
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Keywords: Structure Evolution, Modularity, Learning, neural networks, structure optimization
[igel:01a] Igel, C., W. Erlhagen, and D. Jancke (2001). Optimization of neural field models. Neurocomputing 36(1-4), 225-233.
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Keywords: evolutionary optimization, evolution strategy, gradient-based learning, neural field, neuroscience
[igel:01b] Igel, C. and W. von Seelen (2001). Design of a field model for early vision: A case study of evolutionary algorithms in neuroscience. In 28th Göttingen Neurobiology Conference, Volume 2, pp. 1034. Georg Thieme Verlag.
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Keywords: evolution strategy, neuroscience
[igel:01c] Igel, C. and M. Kreutz (2001). Operator adaptation in structure optimization of neural networks. In L. Spector, E. D. Goodman, A. Wu, W. B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. Garzon, and E. Burke (Eds.), Genetic and Evolutionary Computation Conference (GECCO 2001), San Francisco, pp. 1094. Morgan Kaufmann.
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Keywords: evolutionary structure optimization, operator probabilities, strategy adaptation, neural networks
[ronnewinkel:01a] Ronnewinkel, C., C. O. Wilke, and T. Martinetz (2001). Genetic algorithms in time-dependent environments. In L. Kallel, B. Naudts, and A. Rogers (Eds.), Theoretical Aspects of Evolutionary Computing, Natural Computing Series. Springer Verlag.
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[ronnewinkel:01d] Ronnewinkel, C. and T. Martinetz (2001). Explicit speciation with few a priori parameters for dynamic optimization problems. GECCO 2001, Workshop on `Evolutionary Algorithms for Dynamic Optimization Problems'.
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[stagge:00] Stagge, P. (2001). Strukturoptimierung rückgekoppelter neuronaler Netze. Konzepte neuronaler Informationsverarbeitung. Stuttgart: ibidem-Verlag.
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[stagge:01] Stagge, P. and C. Igel (2001). Structure optimization and isomorphisms. In L. Kallel, B. Naudts, and A. Rogers (Eds.), Theoretical Aspects of Evolutionary Computing, Natural Computing series, pp. 409-422. Springer-Verlag.
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Keywords: competing conventions problem, evolutionary structure optimization, graph isomorphism, neural networks
[vogel:01] Vogel, A. (2001). Ein Ansatz zur Optimierung des Straß enverkehrs auf Knotenebene. Konzepte neuronaler Informationsverarbeitung. Stuttgart: ibidem-Verlag.
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[weinert:01] Weinert, K., O. Webber, A. Busse, M. Hüsken, J. Mehnen, and P. Stagge (2001). Koordinierter Einsatz von Sensorik und Statistik zur Analyse und Modellierung von BTA-Tiefbohrprozessen. Zeitschrift für wirtschaftlichen Fabrikbetrieb 96(5), 262-265.
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[weinert:01b] Weinert, K., O. Webber, A. Busse, M. Hüsken, J. Mehnen, and P. Stagge (2001). Experimental investigation of the dynamics of the BTA deep hole drilling process. Production Engineering - Research and Development in Germany VIII(2).
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[weinert:01c] Weinert, K., O. Webber, M. Hüsken, and J. Mehnen (2001). Statistics and time series analyses of BTA deep hole drilling. In M. Kleiner (Ed.), COST P4, Non-linear Dynamics in Mechanical Processing. EU-Framework COST Action P4, University of Dortmund, Dortmund, Germany.
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[wilke:01a] Wilke, C. O., C. Ronnewinkel, and T. Martinetz (2001). Dynamic fitness landscapes in molecular evolution. Phys. Rep.. In press.
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[wilke:01b] Wilke, C. O. and C. Ronnewinkel (2001). Dynamic fitness landscapes: Expansions for small mutation rates. Physica A 290(3-4), 475-490.
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[kreutz:00b] Kreutz, M., A. M. Busse, and B. Sendhoff (2000, November). Evolution of adaptive nonlinear models. In S.-Y. Lee (Ed.), Seventh International Conference on Neural Information Processing - Proceedings, Volume 2, pp. 885-890.
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Keywords: Adaptive models, evolutionary structure optimization, regularization
[jin:00] Jin, Y. C., W. von Seelen, and B. Sendhoff (2000, February). Extracting interpretable fuzzy rules from rbf neural networks. Internal Report IRINI 00-02, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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[chalimourda:00] Chalimourda, A., B. Schölkopf, and A. Smola (2000). Choosing nu in support vector regression with different noise models - theory and experiments. In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2000). IEEE Computer Society Press.
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[gayko:00] Gayko, J. E. (2000). Datengetriebener Entwurf eines Meßsystems auf der Basis von Körperschallsignalen. Berichte aus der Elektrotechnik. Shaker Verlag.
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[huesken:00a] Hüsken, M., C. Goerick, and A. Vogel (2000). Fast adaptation of the solution of differential equations to changing constraints. In H.-H. Bothe and R. Rojas (Eds.), Proceedings of the Second International ICSC Symposium on Neural Computation (NC 2000), pp. 181-187. ICSC Academic Press.
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[huesken:00b] Hüsken, M., J. E. Gayko, and B. Sendhoff (2000). Optimization for problem classes - neural networks that learn to learn. In X. Yao and D. F. Fogel (Eds.), 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (ECNN 2000), New York, pp. 98-109. IEEE Press.
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Keywords: structure optimization, adaptability, learning
[huesken:00c] Hüsken, M. and C. Goerick (2000). Fast learning for problem classes using knowledge based network initialization. In S.-I. Amari, C. L. Giles, M. Gori, and V. Piuri (Eds.), Proceedings of the International Joint Conference on Neural Networks (IJCNN 2000), Volume VI, Los Alamitos, Carlifornia, USA, pp. 619-624. IEEE Computer Society Press.
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Keywords: structure optimization, adaptability, learning, differential equation
[huesken:00d] Hüsken, M. and B. Sendhoff (2000). Evolutionary optimization for problem classes with lamarckian inheritance. In S.-Y. Lee (Ed.), Seventh International Conference on Neural Information Processing (ICONIP 2000) - Proceedings, Volume 2, pp. 897-902.
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Keywords: Structure optimization, Lamarck, Evolution and Learning
[igel:00a] Igel, C. and M. Hüsken (2000). Improving the rprop learning algorithm. In H.-H. Bothe and R. Rojas (Eds.), Proceedings of the Second International ICSC Symposium on Neural Computation (NC 2000), pp. 115-121. ICSC Academic Press.
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[kreutz:00a] Kreutz, M., D. Hanke, and S. Gehlen (2000). Solving extended hybrid-flow-shop problems using active schedule generation and genetic algorithms. In Proceedings of PPSN VI, Volume VI.
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[kreutz:00c] Kreutz, M. (2000). Modellierung von unvollständig beschriebenen Systemen. ibidem-Verlag. ISBN 3898210790.
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Keywords: Nonlinear statistical models, evolutionary structure optimization, incomplete data
[sendhoff:97c] Sendhoff, B., C. Pötter, and W. von Seelen (2000). The role of information in simulated evolution. In Y. Bar-Yam (Ed.), Unifying themes in complex systems - Proceedings of the International Conference on Complex Systems 1997, pp. 453-470.
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[stagge:00b] Stagge, P. and C. Igel (2000). Neural network structures and isomorphisms: Random walk characteristics of the search space. In X. Yao and D. B. Fogel (Eds.), 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (ECNN), Piscataway, NJ, pp. 82-90. IEEE press.
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Keywords: competing conventions problem, evolutionary structure optimization, graph isomorphism, neural networks
[vogel:00] Vogel, A., C. Goerick, and W. von Seelen (2000). Evolutionary algorithms for optimizing traffic flow. In Proceedings of the European Symposium on Intelligent Techniques. Verlag Mainz, Wissenschaftsverlag Aachen.
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[poetter:99] Pötter, C. (1999, April). Information in Evolutionären Algorithmen und bei der Roboternavigation. Berichte aus der Physik. Shaker Verlag.
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[bergener:99] Bergener, T., C. Bruckhoff, and C. Igel (1999). Evolutionary parameter optimization for visual obstacle detection. In J. Blanc-Talon and D. Popesc (Eds.), Advanced Concepts for Intelligent Vision Systems (ACIVS '99), pp. 104-109. The International Institute for Advanced Studies in Systems Research and Cybernetics.
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[goerick:99] Goerick, C. (1999). How irrelevant inputs affect MLP pattern based learning. In Proceedings of the International Conference on Artificial Neural Networks (ICANN '99).
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[igel:99a] Igel, C. and K. Chellapilla (1999). Investigating the influence of depth and degree of genotypic change on fitness in genetic programming. In W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela, and R. E. Smith (Eds.), Genetic and Evolutionary Computation Conference (GECCO 99), Volume 2, pp. 1061-1068. Morgan Kaufmann.
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[igel:99b] Igel, C. and M. Kreutz (1999). Using fitness distributions to improve the evolution of learning structures. In V. W. Porto (Ed.), Congress on Evolutionary Computation (CEC 99), Volume 3, Piscataway, NJ, pp. 1902-1909. IEEE Press.
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Keywords: genetic programming, mixture models, operator probabilities, strategy adaptation
[igel:99c] Igel, C. and K. Chellapilla (1999). Fitness distributions: Tools for designing efficient evolutionary computations. In L. Spector, W. B. Langdon, U.-M. O'Reilly, and P. J. Angeline (Eds.), Advances in Genetic Programming, Volume 3, Chapter 9, pp. 191-216. MIT Press.
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[jin:99a] Jin, Y. C., W. von Seelen, and B. Sendhoff (1999). On generating fc3 fuzzy rule systems from data using evolution strategies. IEEE Transactions Systems, Man and Cybernetics, Part B: Cybernetics 29(4), 829-845.
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[jin:99b] Jin, Y. C. and B. Sendhoff (1999). Knowledge incorporation into neural networks from fuzzy rules. Neural Processing Letters 10(3), 231-242.
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[jin:99c] Jin, Y. C. and W. von Seelen (1999). Evaluating flexible structured fuzzy controllers via evolution strategies. International Journal of Fuzzy Sets and Systems 286(1), 97-156.
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[kreutz:99a] Kreutz, M., A. M. Reimetz, B. Sendhoff, C. Weihs, and W. von Seelen (1999, January). Structure optimization of density estimation models applied to regression problems with dynamic noise. In D. Heckerman and J. Whittaker (Eds.), Proceedings of the 7th International Workshop on Artificial Intelligence and Statistics, San Mateo, CA, pp. 237-242. Morgan Kaufmann.
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Keywords: Density estimation, evolutionary structure optimization, time series prediction, dynamic noise
[kreutz:99b] Kreutz, M., A. M. Reimetz, B. Sendhoff, C. Weihs, and W. von Seelen (1999). Regularization and model selection in the context of density estimation. Technischer Bericht 27/1999, SFB 475, Fachbereich Statistik, Universität Dortmund, 44221 Dortmund, Germany.
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Keywords: Model selection, regularization, density estimation
[samanpour:99] Samanpour, A. (1999). Strukturfindung von Prädiktionssystemen - Multiexpertensysteme und Evolutionsstrategien. Berichte aus der Physik. Shaker-Verlag.
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[sendhoff:99a] Sendhoff, B. and M. Kreutz (1999). Variable encoding of modular neural networks for time series prediction. In V. W. Porto (Ed.), Congress on Evolutionary Computation (CEC'99), Volume 1, pp. 259-266. IEEE Press, New York.
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[sendhoff:99c] Sendhoff, B. and M. Kreutz (1999). A model for the dynamic interaction between evolution and learning. Neural Processing Letters 10(3), 181-193.
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[stagge:99a] Stagge, P. and B. Sendhoff (1999). Organisation of past states in recurrent neural networks: Implicit embedding. In M. Mohammadian (Ed.), International Conference on Computational Intelligence for Modelling Control and Automation, pp. 21-27.
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[wilke:99] Wilke, C. O., C. Ronnewinkel, and T. Martinetz (1999). Molecular evolution in time-dependent environments. In D. Floreano, J.-D. Nicoud, and F. Mondada (Eds.), Advances in Artificial Life, ECAL'99, Lausanne, Lecture Notes in Artificial Intelligence. Springer Verlag.
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[zhuang:99] Zhuang, Q. (1999). Optimierung eines Fuzzy-Fahrreglers mit Hilfe der Evolutionsstrategie. In Fortschritt-Berichte VDI, Number 804 in Reihe 8. VDI Verlag GmbH.
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[sendhoff:99b] Sendhoff, B. (1998, sep). Evolution of Structures - Optimization of Artificial Neural Structures for Information Processing. Berichte aus der Physik. Shaker Verlag. ISBN 3-8265-4155-3.
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[zhuang:98c] Zhuang, Q., M. Kreutz, and J. E. Gayko (1998, July). Evolutionäre Optimierung von Fuzzy-Systemen mit variabler Kodierung. Internal Report IRINI 98-07, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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[gayko:98] Gayko, J. E. (1998, May). Reifendruckschätzung mit Hilfe der Körperschallanalyse. Internal Report IRINI 98-05, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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[zhuang:98a] Zhuang, Q., M. Kreutz, and J. Gayko (1998, March). Optimization of a fuzzy system using evolutionary algorithms. In W. Brauer (Ed.), Proceedings of the Fuzzy-Neuro-Systems 98, pp. 178-185.
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[zhuang:98b] Zhuang, Q., M. Kreutz, and J. E. Gayko (1998, March). Optimization of a fuzzy controller for a driver assistant system. In W. Brauer (Ed.), Proceedings of the Fuzzy-Neuro-Systems 98, pp. 376-382.
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[goerick:98b] Goerick, C. (1998, February). Considerations of the gain spectrum. Internal Report IRINI 98-02, Institut für Neuroinformatik.
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[igel:01d] Igel, C. and M. Kreutz (1998, feb). Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. Internal Report IRINI 01-03, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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Keywords: evolutionary structure optimization, operator probabilities, strategy adaptation, neural networks
[goerick:98a] Goerick, C. (1998). Beiträge zur Theorie der Lerndynamik künstlicher neuronaler Netze. Number 557 in Informatik und Kommunikationstechnik. VDI Verlag GmbH.
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[igel:98a] Igel, C. (1998). Causality of hierarchical variable length representations. In Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC'98), pp. 324-329. IEEE Press.
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[jin:98] Jin, Y. C., W. von Seelen, and B. Sendhoff (1998). An approach to rule-based knowledge extraction. In IEEE International Conference on Fuzzy Systems, Anchorage, Alaska, pp. 1188-1993.
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[kreutz:98] Kreutz, M., A. M. Reimetz, B. Sendhoff, C. Weihs, and W. von Seelen (1998). Optimisation of density estimation models with evolutionary algorithms. In A. E. Eiben, T. Bäck, M. Schoenauer, and H. P. Schwefel (Eds.), Parallel Problem Solving from Nature - PPSN V, Number 1498 in Lecture Notes in Computer Science, Berlin, pp. 998-1007. Springer Verlag.
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Keywords: Density estimation, mixture models, evolutionary algorithms, structure optimization
[poetter:98] Pötter, C. (1998). Information-theoretic analysis of a mobile agent's learning in a discrete state space. In A. E. Eiben, T. Bäck, M. Schoenauer, and H. P. Schwefel (Eds.), Proceedings of Parallel Problem Solving from Nature - PPSN V, Number 1498 in Lecture Notes in Computer Science. Springer Verlag.
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[reimetz:98] Reimetz, A. M. (1998). Strukturbestimmung von probabilistischen neuronalen Netzen mit Hilfe von Evolutionären Algorithmen. Diplomarbeit, University of Dortmund, Department of Statistics.
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Keywords: ensity estimation, structure optimization, mixture models, evolutionary algorithms
[sendhoff:98a] Sendhoff, B. (1998). Evolution of Structures - Optimization of Artificial Neural Structures for Information Processing. Phd thesis, physics, Ruhr-University of Bochum, Institute for Neuroinformatics, Department of Physik, Ruhr-Universität Bochum, D-44780 Bochum (Germany).
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[sendhoff:98b] Sendhoff, B. and M. Kreutz (1998). Evolutionary optimization of the structure of neural networks using a recursive mapping as encoding. In G. Smith, N. Steele, and R. Albrecht (Eds.), Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms (ICANNGA'97), pp. 370-374. Springer Verlag.
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[stagge:98] Stagge, P. (1998). Averaging efficiently in the presence of noise. In A. E. Eiben, T. Bäck, M. Schoenauer, and H. P. Schwefel (Eds.), Parallel Problem Solving from Nature - PPSN V, Number 1498 in Lecture Notes in Computer Science, pp. 188-197. Springer Verlag.
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[zhuang:97] Zhuang, Q. and M. Kreutz (1997, November). Optimierung eines Fuzzy-Sugeno-Systems. Internal Report IRINI 97-11, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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[sievers:97] Sievers, C., M. Kreutz, and B. Sendhoff (1997, March). Modulverwaltung und Kommunikation in PAMPER - (P)arallel (A)nd (M)odular (P)rogramming (E)nvi(r)onment. Internal Report IRINI 97-04, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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[kreutz:97] Kreutz, M., C. Sievers, A. Dietrich, and B. Sendhoff (1997, February). A programmers guide to PAMPER - classes & tools - (P)arallel (A)nd (M)odular (P)rogramming (E)nvi(r)onment. Internal Report IRINI 97-03, Institut für Neuroinformatik.
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[gayko:97] Gayko, J. E., R. Lohmann, H. Voss, B. Sendhoff, and T. Zamzow (1997). Application of structure evolution to system state diagnosis. In Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN'97), Stockholm.
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[goerick:97] Goerick, C., B. Sendhoff, and W. von Seelen (1997). From neural networks to neural strategies. In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, (ICASSP'97). IEEE Press.
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[poetter:97] Pötter, C. (1997). Evolutionary learning of autonomous agents with anticipatory capabilities. In First International Conference on Computing Anticipatory Systems (CASYS'97), Liege, Belgium.
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[sendhoff:97a] Sendhoff, B., M. Kreutz, and W. von Seelen (1997). A condition for the genotype-phenotype mapping: Causality. In T. Bäck (Ed.), Proceedings of the Seventh International Conference on Genetic Algorithms (ICGA'97), San Francisco, USA.
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[sendhoff:97b] Sendhoff, B., M. Kreutz, and W. von Seelen (1997). Causality and the analysis of local search in evolutionary algorithms. Internal Report IRINI 97-16, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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[stagge:97] Stagge, P. and B. Sendhoff (1997). An extended elman net for modeling time series. In W. Gerstner, A. Germond, M. Hasler, and J. Nicoud (Eds.), Proceedings of the International Conference on Artificial Neural Networks (ICANN'97), Volume 1327 of Lecture Notes in Computer Science, pp. 427-432. Springer Verlag.
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[sendhoff:96] Sendhoff, B. and M. Kreutz (1996, September). Analysis of possible genome-dependence of mutation rates in genetic algorithms. In T. C. Fogarty (Ed.), Evolutionary Computing - Selected Papers from the 1996 AISB Workshop, Volume 1134 of Lecture Notes in Computer Science, pp. 257-269. Springer Verlag.
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[gayko:96] Gayko, J. E. and C. Goerick (1996). Artificial neural networks for tyre pressure estimation. In Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN'96), London, GB.
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[goerick:96a] Goerick, C. and T. Rodemann (1996). Evolution strategies: An alternative to gradient based learning. In Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN'96).
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Keywords: evolution strategy, learning
[goerick:96b] Goerick, C. and W. von Seelen (1996). On unlearnable problems or a model for premature saturation in backpropagation learning. In Proceedings of the European Symposium on Artificial Neural Networks, ESANN'96.
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[poetter:96a] Pötter, C. (1996). Path planning for autonomous vehicles. In Proceedings of the World Automation Congress (WAC'96), Volume 3, pp. 653-658.
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[poetter:96b] Pötter, C. (1996). Optimierung der Fahrwegplanung eines Roboters mit Hilfe von Evolutionsstrategien. Internal Report IRINI 96-01, Institut für Neuroinformatik.
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[wacquant:96] Wacquant, S. and F. Joublin (1996). Inward relearning: A step towards long-term memory. In C. von der Malsburg, W. von Seelen, J. C. Vorbrueggen, and B. Sendhoff (Eds.), Proceedings of the ICANN 1996, pp. 887-892. Springer-Verlag.
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[wienholt:96] Wienholt, W. and B. Sendhoff (1996, January). How to determine the redundancy of noisy chaotic time series. International Journal of Bifurcation and Chaos 6(1), 101-117.
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[wienholt:95] Wienholt, W. (1995, March). Stapeloptimierung einer Haubenglühanlage mithilfe von Evolutionsstrategien - eine Machbarkeitsuntersuchung. Internal report, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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[goerick:95a] Goerick, C. (1995). On efficiently monitoring the learning process of feedforward neural networks. In ICANN'95, Proceedings of the International Conference on Artificial Neural Networks.
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[goerick:95b] Goerick, C. (1995). Über nicht lernbare Probleme oder Ein Modell für die vorzeitige Sättigung bei vorwärtsgekoppelten Neuronalen Netzen. In Mustererkennung 1994, Proceedings of the 17. Symposium of the DAGM.
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[sendhoff:95] Sendhoff, B. and M. Kreutz (1995). Variable, genom dependent mutation probability for genetic algorithms. Internal Report IRINI 95-07, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany.
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[wienholt:94] Wienholt, W. (1994). Improving a fuzzy inference system by means of evolution strategy. In B. Reusch (Ed.), Fuzzy Logik, pp. 186-195. Berlin, Germany: Springer Verlag.
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[wienholt:93a] Wienholt, W. (1993). A refined genetic algorithm for parameter optimization problems. In S. Forrest (Ed.), Genetic Algorithms: Proceedings of the Fifth International Conference (GA93), San Mateo, CA, pp. 589-596. Morgan Kaufmann Publishers.
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[wienholt:93b] Wienholt, W. (1993). Minimizing the system error in feedforward neural networks with evolution strategy. In S. Gielen and B. Kappen (Eds.), Proceedings of the International Conference on Artificial Neural Networks, London, GB, pp. 490-493. Springer Verlag.
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[wienholt:93c] Wienholt, W. (1993). Optimizing the structure of radial basis function networks by optimizing fuzzy inference systems with evolution strategy. Internal Report IRINI 93-07, Institut für Neuroinformatik.
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 Last Update 2009-06-18 by <Christian.Igel@neuroinformatik.ruhr-uni-bochum.de>