By R. Riolo, et al
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Additional resources for Genetic Programming Theory and Practice V
There are three reference runs: PGP with the population size 100, and 250 generations, PGPA with twice the number of generations, and PGPB with twice the population size of the PGP runs. 327 276610 271850 268876 268201 268379 250000 Soft Evolution of Robust Regression Models 27 Figure 2-5. Summary of Results for the Kotanchek problem. The bubbles represent the results of the different experiments in Cases 1–3 in terms of the median performance measure over 50 independent runs (y-axis), interquartile range of the performance measure (x-axis), and the normalized total number of function evaluations per run (the size of the bubbles).
Background Ever since the inception of contemporary evolutionary algorithms in Hollands seminal work, (Holland, 1975), the proliferation of a single dominant solution throughout the population and the consequent evolutionary gridlock it results in, has been recognised as a core concern of the science. This sec- Manipulation of Convergence in Evolutionary Systems 35 tion reviews some of the work done to address this issue and the nature of the resulting strategies produced. Using the ﬁtness of the population as a mechanism to prevent premature convergence was one of the ﬁrst such strategies developed in; (Goldberg and Richardson, 1987).
These pools can only be maintained by their being continually replenished with positive feedback from successful crossover events. This accounts for the systems resistance to convergence as evidenced by the improved 42 GENETIC PROGRAMMING THEORY AND PRACTICE V Best Fitness Comparison, Age Based System 26 25 24 23 Fitness 22 21 20 19 18 age based system, initial pop 100 std GP, tournament size 2, pop 1000 17 0 50000 100000 150000 200000 250000 300000 Evaluations 350000 400000 450000 500000 Figure 3-4.
Genetic Programming Theory and Practice V by R. Riolo, et al