Jonathan C. Brant and Kenneth O. Stanley (2020)
Diversity Preservation in Minimal Criterion Coevolution through Resource Limitation.
In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2020). New York, NY: ACM (8 pages).
Minimal Criterion Coevolution (MCC) is a recently-introduced algorithm that demonstrates how interactions between two populations, each subject to a simple reproductive constraint, can produce an open-ended search process. Unlike conventional quality diversity (QD) algorithms, which also promote divergence, MCC does not require an explicit characterization of behavior or a comparison of performance, thereby addressing bottlenecks introduced by an intrinsically finite behavior descriptor and by an assessment of comparative quality. Genetic speciation, a common method of diversity preservation, maintains population diversity in MCC; however, it requires an unnatural explicit comparison of genetic similarity. In nature, organisms are implicitly segregated into niches that each have a carrying capacity dictated by the amount of available resources. To show that MCC can be simpler and more natural while still working effectively, this paper introduces a method of diversity preservation through resource limitation, thereby alleviating the need to formalize and compare genetic distance. Experimental results in a maze navigation domain demonstrate that resource limitation not only maintains higher population diversity in both the maze and agent populations, but also accelerates evolution by forcing individuals to explore new niches, thereby suggesting that resource limitation is an effective, simpler, and more natural alternative for diversity preservation in MCC.