Reachability Analysis for Lexicase Selection via Community Assembly Graphs

Fitness landscapes have historically been a powerful tool for analyzing the search space explored by evolutionary algorithms. In particular, they facilitate understanding how easily reachable an optimal solution is from a given starting point. However, simple fitness landscapes are inappropriate for...

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Bibliographic Details
Published in:arXiv.org 2023-09
Main Authors: Dolson, Emily, Lalejini, Alexander
Format: Article
Language:English
Subjects:
Assembly
Evolutionary algorithms
Fitness
Genetic algorithms
Graphs
Toolkits
Online Access:Get full text
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Summary:Fitness landscapes have historically been a powerful tool for analyzing the search space explored by evolutionary algorithms. In particular, they facilitate understanding how easily reachable an optimal solution is from a given starting point. However, simple fitness landscapes are inappropriate for analyzing the search space seen by selection schemes like lexicase selection in which the outcome of selection depends heavily on the current contents of the population (i.e. selection schemes with complex ecological dynamics). Here, we propose borrowing a tool from ecology to solve this problem: community assembly graphs. We demonstrate a simple proof-of-concept for this approach on an NK Landscape where we have perfect information. We then demonstrate that this approach can be successfully applied to a complex genetic programming problem. While further research is necessary to understand how to best use this tool, we believe it will be a valuable addition to our toolkit and facilitate analyses that were previously impossible.
ISSN:2331-8422
DOI:10.48550/arxiv.2309.10973