The CIOP team is proud to announce that the latest version (V 0.9.0, February 2013) of the Tuned Data Mining in R (TDMR) package is now available for download on the Comprehensive R Archive Network (CRAN).
Download the new released version from this link.
Title: Self-Adaptive Algorithms for Finding Robust Optima: Promises and Limitations
Time: Fr., Oct, 26th, 2012, 11:00-11:45,
Place: Room 0.214
Many problems in engineering design deal with locating optimal parameter configurations for systems. Evolution strategies provide a robust framework for this. This talk deals with the question of how we can find optima that are robust to stochastic perturbations of the input variables and to noise on the output variables. A bifurcation-based classification of types of robust optima is provided, viewing the integration of robustness as a Weierstrass transformation. Based on dynamical systems analysis of evolution strategies the limits of self-adaptive schemes for controlling the sample size of self-adaptive robust evolution strategies are shown. Finally, some recently developed efficient archiving and modeling strategies for speeding up optimization with costly evaluations are highlighted.
Publication: Wolfgang Konen, Patrick Koch, How slow is slow? SFA detects signals that are slower than the driving force, In: B. Filipic, J. Silc (eds.), Proc. 4th Int. Conf. on Bioinspired Optimization Methods and their Applications, BIOMA 2010, May 2010, Ljubljana, Slovenia (PDF)
Publication: Oliver Flasch, Thomas Bartz-Beielstein, Artur Davtyan, Patrick Koch and Wolfgang Konen, Comparing SPO-tuned GP and NARX Prediction Models for Stormwater Tank Fill Level Prediction. In P. Sobrevilla (ed.), Proc. WCCI, July 2010, Barcelona (PDF)