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Found 6 papers, 4 papers with code
Does mapping elites illuminate search spaces? A large-scale user study of MAP--Elites applied to human--AI collaborative design
Although there is some evidence that the MAP-Elites provide higher-quality individual recommendations, neither study provides convincing evidence that these recommendations have a more positive influence on the design process than simply a random selection of designs.
MBORE: Multi-objective Bayesian Optimisation by Density-Ratio Estimation
In this work we present MBORE: multi-objective Bayesian optimisation by density-ratio estimation, and compare it to BO across a range of synthetic and real-world benchmarks.
Evaluating Mixed-Initiative Procedural Level Design Tools using a Triple-Blind Mixed-Method User Study
A rigorous user study was designed which compared the experiences of designers using the mixed-initiative tool to designers who were given a tool which provided completely random level suggestions.
$ε$-shotgun: $ε$-greedy Batch Bayesian Optimisation
Bayesian optimisation is a popular, surrogate model-based approach for optimising expensive black-box functions.
Greed is Good: Exploration and Exploitation Trade-offs in Bayesian Optimisation
The performance of acquisition functions for Bayesian optimisation to locate the global optimum of continuous functions is investigated in terms of the Pareto front between exploration and exploitation.
Bayesian Search for Robust Optima
We propose a method for robust optimisation using Bayesian optimisation to find a region of design space in which the expensive function's performance is relatively insensitive to the inputs whilst retaining a good quality.
