Publication 2023
BOP-Elites
A Bayesian Optimisation Approach to Quality Diversity Search with Black-Box descriptor functions
Fig. 3. A visualisation of the BOP-Elites algorithm
Abstract
BOP-Elites: A Bayesian Optimisation Approach to Quality Diversity Search with Black-Box descriptor functions
Paul Kent, Adam Gaier, Juergen Branke, Jean-Baptiste Mouret
Quality Diversity (QD) algorithms such as MAP-Elites are a class of optimisation techniques that attempt to find many high performing points that all behave differently according to a user-defined behavioural metric. In this paper we propose the Bayesian Optimisation of Elites (BOP-Elites) algorithm. Designed for problems with expensive black-box objective and behaviour functions, it is able to return a QD solution-set after a relatively small number of samples. BOP-Elites models both objective and behavioural descriptors with Gaussian Process surrogate models and uses Bayesian Optimisation strategies for choosing points to evaluate in order to solve the quality-diversity problem. In addition, BOP-Elites produces high quality surrogate models which can be used after convergence to predict solutions with any behaviour in a continuous range. An empirical comparison shows that BOP-Elites significantly outperforms other state-of-the-art algorithms without the need for problem-specific parameter tuning.
Download publicationAssociated Researchers
Paul Kent
Warwick University
Jean-Baptiste Mouret
Inria, CNRS, Université de Lorraine
Juergen Branke
Warwick Business School
Related Resources
2024
Recently Published by Autodesk ResearchersA selection of papers published recently by Autodesk Researchers…
2024
Exploring Opportunities for Adopting Generative AI in Automotive Conceptual DesignThis research discusses opportunities for adopting generative AI in…
2024
Experiential Views: Towards Human Experience Evaluation of Designed Spaces using Vision-Language ModelsExploratory research on helping designers and architects anticipate…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us