Mixture-模型 (Model) Preference 学习 (Learning) for Many-Objective 贝叶斯 (Bayesian) 优化 (Optimization)

Mixture-Model Preference Learning for Many-Objective Bayesian Optimization

Preference-based many-objective optimization faces two obstacles: an expanding space of trade-offs and heterogeneous, context-dependent human value structures. Towards this, we propose a Bayesian framework that learns a small set of latent preference archetypes rather than assuming a single fixed utility function, modelling them as components of a Dirichlet-process mixture with uncertainty over both archetypes and their weights. To query efficiently, we designing hybrid queries that target infor