A Bayesian Optimisation Approach to Quality Diversity Search with Black-Box descriptor functions

Fig. 3. A visualisation of the BOP-Elites algorithm


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 publication

Associated Researchers

Paul Kent

Warwick University

Jean-Baptiste Mouret

Inria, CNRS, Université de Lorraine

Juergen Branke

Warwick Business School

View all researchers

Related Resources



Neural Shape Diameter Function for Efficient Mesh Segmentation

Introducing a neural approximation of the Shape Diameter Function,…



Simulation-Based Architectural Design

In recent decades, architects have turned to computer simulation with…



Data Visualization and Visual Analytics

Visual data representations leverage the power of human perception to…



3D User Interfaces: Human Experience in 3D Environments

Designing user interfaces for interacting with 3D data involves a…

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