Turning Genes Off and On: Using Genetic Algorithms with Complexity-Based Fitness for Model Selection in Ecology
نویسندگان
چکیده
This paper describes experiments with a genetic algorithm that combines parsimony with a novel gene regulation mechanism to carry out model selection. In effect, the GA orchestrates a competition among a community of models. Parsimony is implemented via the Akaike Information Criterion, and gene regulation uses a modulo function to overload the gene values. The approach is shown to be successful with polynomial models and complex biological simulation models, even when Gaussian noise is added to the data.
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