Abstract
We use an adversarial approach inspired by biological coevolution to generate complex line drawings without human guidance. Artificial artists and critics work against each other in an iterative competitive framework, forcing each to become increasingly sophisticated to outplay the other. Both the artists and critics are implemented in hercl, a framework combining linear and stack-based Genetic Programming, which is well suited to coevolution because the number of competing agents is kept small while still preserving diversity. The aesthetic quality of the resulting images arises from the ability of the evolved hercl programs, making judicious use of register adjustments and loops, to produce repeated substructures with subtle variations, in the spirit of low-complexity art.
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Vickers, D., Soderlund, J., Blair, A. (2017). Co-Evolving Line Drawings with Hierarchical Evolution. In: Wagner, M., Li, X., Hendtlass, T. (eds) Artificial Life and Computational Intelligence. ACALCI 2017. Lecture Notes in Computer Science(), vol 10142. Springer, Cham. https://doi.org/10.1007/978-3-319-51691-2_4
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DOI: https://doi.org/10.1007/978-3-319-51691-2_4
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