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I am writing a thesis about automatic GUI testing. In order to find the fittest strategy I am using GP. I am using tournament selection to select chromosomes for the next generation and elitism to make sure the strongest elite(s) will proceed to the next round.

Basically, I have 2 questions:

a) Many papers use 7 as tournament size because this is the default in one of Koza's papers. From my understanding we are missing the point of Koza. I think 7 might have been a good fit for his research, which may be based on his population. Shouldn't we use the probability and adjust the tournament size accordingly instead? As one may already have noticed, I am making assumptions. Are there papers I may have missed that are writing about choosing the right tournament size? If not, should experiments be conducted to find the right tournament size for a specific research setup?

Eg. Following results in a probability of 7% that a chromosome is part of the tournament.

Population: 100 Elites: 5 Tournament selection: 7

Increasing the tournament size (selection pressure) will result in a higher probability a chromosome will be selected for the tournament.

b) If I have a population of 100, a tournament size of 10 and 5 elites, if I understand correctly, 6 chromosomes will make it to the next generation right?

Please people, enlighten me :)

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