Applying Ecological Principles to Genetic Programming Emily Dolson and Wolfgang Banzhaf and Charles Ofria Abstract In natural ecologies, niches are created, altered, or destroyed, driving pop- ulations to continually change and produce novel features. Here, we explore an ap- proach to guiding evolution via the power of niches: ecologically-mediated hints. The original exploration of ecologically-mediated hints occurred in Eco-EA, an al- gorithm 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 lim- ited 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 fit- ness 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. lexi- case selection) dramatically impacts the algorithm’s robustness to misleading hints. Emily Dolson BEACON Center for the Study of Evolution in Action and Department of Computer Science and Ecology, Evolutionary Biology, and Behavior Program, Michigan State University, East Lansing, MI, USA e-mail: dolsonem@msu.edu Wolfgang Banzhaf BEACON Center for the Study of Evolution in Action and Department of Computer Science, Michigan State University, East Lansing, MI, USA e-mail: banzhafw@msu.edu Charles Ofria BEACON Center for the Study of Evolution in Action and Department of Computer Science and Ecology, Evolutionary Biology, and Behavior Program, Michigan State University, East Lansing, MI, USA e-mail: ofria@msu.edu 1