Large Language Models as In-context AI Generators for Quality-Diversity

arXiv:2404.15794v1 Announce Type: cross
Abstract: Quality-Diversity (QD) approaches are a promising direction to develop open-ended processes as they can discover archives of high-quality solutions across diverse niches. While already successful in many applications, QD approaches usually rely on combining only one or two solutions to generate new candidate solutions. As observed in open-ended processes such as technological evolution, wisely combining large diversity of these solutions could lead to more innovative solutions and potentially boost the productivity of QD search. In …

abstract ai generators applications archives arxiv context cs.ai cs.lg cs.ne diverse diversity generate generators language language models large language large language models processes quality solutions type while