Self-Referential Quality Diversity Through Differential Map-Elites

Tae Jong Choi; Julian Togelius

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arXiv · 2107.04964

Self-Referential Quality Diversity Through Differential Map-Elites

Tae Jong Choi·Julian Togelius

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Abstract

Differential MAP-Elites is a novel algorithm that combines the illumination capacity of CVT-MAP-Elites with the continuous-space optimization capacity of Differential Evolution. The algorithm is motivated by observations that illumination algorithms, and quality-diversity algorithms in general, offer qualitatively new capabilities and applications for evolutionary computation yet are in their original versions relatively unsophisticated optimizers. The basic Differential MAP-Elites algorithm, introduced for the first time here, is relatively simple in that it simply combines the operators from Differential Evolution with the map structure of CVT-MAP-Elites. Experiments based on 25 numerical optimization problems suggest that Differential MAP-Elites clearly outperforms CVT-MAP-Elites, finding better-quality and more diverse solutions.

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Tae Jong Choi, Julian Togelius. 2021-07-11. Self-Referential Quality Diversity Through Differential Map-Elites. https://arxiv.org/abs/2107.04964

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