Abstract
Artificial selection of microbial ecosystems for their collective function has been shown to be effective in laboratory experiments. In previous work, we used evolutionary simulation models to understand the mechanistic basis of the observed ecosystem-level response to artificial selection. Here we extend this work to consider artificial ecosystem selection as a method for evolutionary optimisation. By allowing solutions involving multiple species, artificial ecosystem selection adds a new class of multi-species solution to the available search space, while retaining all the single-species solutions achievable by lower-level selection methods. We explore the conditions where multi-species solutions (that necessitate higher-level selection) are likely to be found, and discuss the potential advantages of artificial ecosystem selection as an optimisation method.
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Williams, H.T.P., Lenton, T.M. (2007). Artificial Ecosystem Selection for Evolutionary Optimisation. In: Almeida e Costa, F., Rocha, L.M., Costa, E., Harvey, I., Coutinho, A. (eds) Advances in Artificial Life. ECAL 2007. Lecture Notes in Computer Science(), vol 4648. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74913-4_10
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DOI: https://doi.org/10.1007/978-3-540-74913-4_10
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