Abstract
In this paper we discuss Evolution Strategies within the context of interactive optimization. Different modes of interaction will be classified and compared. A focus will be on the suitability of the approach in cases, where the selection of individuals is done by a human user based on subjective evaluation. We compare the convergence dynamics of different approaches and discuss typical patterns of user interactions observed in empirical studies.
The discussion of empirical results will be based on a survey conducted via the world wide web. A color (pattern) redesign problems from literature will be adopted and extended. The simplicity of the chosen problems allowed us to let a larger number of people participate in our study. The amount of data collected makes it possible to add statistical support to our hypothesis about the performance and behavior of different Interactive Evolution Strategies and to figure out high-performing instantiations of the approach.
The behavior of the user was also compared to a deterministic selection of the best individual by the computer. This allowed us to figure out how much the convergence speed is affected by noise and to estimate the potential for accelerating the algorithm by means of advanced user interaction schemes.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Angeline, P.J.: Evolving fractal movies. In: 1st annual conference on generic programming (Stanford, CA, USA), pp. 503–511 (1996)
Anderson, J.R.:: Cognitive Psychology and its implications. Worth Publishers, UK (2004)
Bäck, T.: Evolutionary Algorithms in Theory and Practice. Oxford University Press, New York (1996)
Banzhaf, W.: Interactive evolution. In: Bäck, T., Fogel, D., Michalewicz, Z. (eds.) Handbook of Evolutionary Computation, ch. C2.10, pp. 1–5. Oxford University Press, Oxford (1997)
Beyer, H.-G.: The Theory of Evolution Strategies. Springer, Berlin (2001)
Dix, A., Finlay, J., Abouwd, G.D., Beale, R.: Human Computer Interaction, 3rd edn. Pearson Education, London (2003)
Filipic, B., Juricic, D.: An interactive genetic algorithm for controller parameter optimization. In: Intl. Conf. on Artificial Neural Nets and Genetic Algorithms, Innsbruck, Austria, pp. 458–462 (2003)
Hansen, N., Ostermeier, A.: Completley Derandomized Selfadaptation in Evolution Strategies. Evolutionary Computation 9(2), 159–195 (2001)
Herdy, M.: Evolution strategies with subjective selection. In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN 1996. LNCS, vol. 1141, Springer, Heidelberg (1996)
Herdy, M.: Evolutionary optimization based on subjective selection – evolving blends of coffee. In: 5th european congress on Intelligent Techniques and Soft Computing EUFIT 1997, pp. 640–644 (1997)
Horowitz: Generating rhythms with genetic algorithms. In: Int. Computer Music Conference (ICMC 1994), pp. 142–143. Aarhus, Denmark (1994)
Parmee, I.C., Bonham, C.R.: Cluster oriented genetic algorithms to support designer/ evolutionary computation. In: Proc. of CEC 1999, Washington D.C., USA, pp. 546–55 (1999)
Reason, J.: Human Error. Cambridge University Press, Cambridge (1990)
Rechenberg, I.: Evolutionsstrategie 1994. Frommann-holzboog, Stuttgart (1994)
Rudolph, G.: On Interactive Evolutionary Algorithms and Stochastic Mealy Automata. In: Ebeling, W., Rechenberg, I., Voigt, H.-M., Schwefel, H.-P. (eds.) PPSN 1996. LNCS, vol. 1141, pp. 218–226. Springer, Heidelberg (1996)
Schwefel, H.-P.: Evolution and Optimum Seeking. Wiley, NY (1995)
Takagi, H.: Interactive Evolutionary Computation: Fusion of the Capabilities of EC Optimization and Human Evaluation. Proceedings of the IEEE 89(9), 1275–1296 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Breukelaar, R., Emmerich, M., Bäck, T. (2006). On Interactive Evolution Strategies. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_51
Download citation
DOI: https://doi.org/10.1007/11732242_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33237-4
Online ISBN: 978-3-540-33238-1
eBook Packages: Computer ScienceComputer Science (R0)