Part of the Natural Computing Series book series (NCS)
KeywordsProgress Rate Subset Selection Threshold Selection Correct Selection Threshold Acceptance
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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8.6 Further Reading
- Bechhofer, R. E., Santner, T. J., & Goldsman, D. M. (1995). Design and Analysis of Experiments for Statistical Selection, Screening, and Multiple Comparisons. New York NY: Wiley.Google Scholar
- Beyer, H.-G. (2001). The Theory of Evolution Strategies. Berlin, Heidelberg, New York: Springer.Google Scholar
- Branke, J., Chick, S., & Schmidt, C. (2005). New developments in ranking and selection: An empirical comparison of the three main approaches. In M. E. Kuhl & others (Eds.), Proceedings of the 2005 Winter Simulation Conference (pp. 708–717). Piscataway NJ: IEEE.Google Scholar
- Gigerenzer, G. & Selten, R., Eds. (2002). Bounded Rationality: The Adaptive Toolbox. Cambridge MA: MIT Press.Google Scholar
- Gigerenzer, G., Todd, P. M., & the ABC research group (1999). Simple Heuristics That Make Us Smart. New York NY: Oxford University Press.Google Scholar
- Rubinstein, A. (1998). Modeling Bounded Rationality. Cambridge MA: MIT Press.Google Scholar
- Rudolph, G. (1997a). Convergence Properties of Evolutionary Algorithms. Hamburg, Germany: Kovač.Google Scholar
- Schwefel, H.-P. (1995). Evolution and Optimum Seeking. Sixth-Generation Computer Technology. New York NY: Wiley.Google Scholar
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