Fitnessless Coevolution. Jaśkowski, W., Wieloch, B., Krawiec, K., & et al , M. K. In *GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation*, pages 355--362, jul, 2008. Association for Computing Machinery. Paper abstract bibtex We introduce fitnessless coevolution (FC), a novel method of comparative one-population coevolution. FC plays games between individuals to settle tournaments in the selection phase and skips the typical phase of evaluation. The selection operator applies a single-elimination tournament to a randomly drawn group of individuals, and the winner of the final round becomes the result of selection. Therefore, FC does not involve explicit fitness measure. We prove that, under a condition of transitivity of the payoff matrix, the dynamics of FC is identical to that of the traditional evolutionary algorithm. The experimental results, obtained on a diversified group of problems, demonstrate that FC is able to produce solutions that are equally good or better than solutions obtained using fitness-based one-population coevolution with different selection methods.

@inproceedings{ jaskowski08fitnessless,
author = {Wojciech Jaśkowski and Bartosz Wieloch and Krzysztof Krawiec and Maarten Keijzer et al},
title = {Fitnessless Coevolution},
abstract = {We introduce fitnessless coevolution (FC), a novel method of comparative one-population coevolution. FC plays games between individuals to settle tournaments in the selection phase and skips the typical phase of evaluation. The selection operator applies a single-elimination tournament to a randomly drawn group of individuals, and the winner of the final round becomes the result of selection. Therefore, FC does not involve explicit fitness measure. We prove that, under a condition of transitivity of the payoff matrix, the dynamics of FC is identical to that of the traditional evolutionary algorithm. The experimental results, obtained on a diversified group of problems, demonstrate that FC is able to produce solutions that are equally good or better than solutions obtained using fitness-based one-population coevolution with different selection methods.},
booktitle = {GECCO '08: Proceedings of the 10th annual conference on Genetic and evolutionary computation},
month = {jul},
organization = {Association for Computing Machinery},
pages = {355--362},
url = {http://www.cs.put.poznan.pl/wjaskowski/pub/papers/jaskowski08fitnessless.pdf} ,
year = {2008}
}

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