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Applying Ecological Principles to Genetic Programming

Part of the Genetic and Evolutionary Computation book series (GEVO)

Abstract

In natural ecologies, niches are created, altered, or destroyed, driving populations to continually change and produce novel features. Here, we explore an approach to guiding evolution via the power of niches: ecologically-mediated hints. The original exploration of ecologically-mediated hints occurred in Eco-EA, an algorithm in which an experimenter provides a primary fitness function for a tough problem that they are trying to solve, as well as “hints” that are associated with limited resources. We hypothesize that other evolutionary algorithms that create niches, such as lexicase selection, can be provided hints in a similar way. Here, we use a toy problem to investigate the expected benefits of using this approach to solve more challenging problems. Of course, since humans are notoriously bad at choosing fitness functions, user-provided advice may be misleading. Thus, we also explore the impact of misleading hints. As expected, we find that informative hints facilitate solving the problem. However, the mechanism of niche-creation (Eco-EA vs. lexicase selection) dramatically impacts the algorithm’s robustness to misleading hints.

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Fig. 5.1

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Correspondence to Emily Dolson .

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Dolson, E., Banzhaf, W., Ofria, C. (2018). Applying Ecological Principles to Genetic Programming. In: Banzhaf, W., Olson, R., Tozier, W., Riolo, R. (eds) Genetic Programming Theory and Practice XV. Genetic and Evolutionary Computation. Springer, Cham. https://doi.org/10.1007/978-3-319-90512-9_5

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  • DOI: https://doi.org/10.1007/978-3-319-90512-9_5

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