Author

Paul Brunzema

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Review Sep 2026

A Decade of Bayesian Optimization for Controller Tuning and Robot Learning: Tutorial, Review, and Future Prospects

A unified perspective on the current landscape of BO is provided, emphasizing its relevance to control systems and robotics, and it highlights future prospects by identifying key research challenges and promising avenues for advancing BO in the field.

David Stenger, Paul Brunzema, Johanna Menn et al. · 1 citation

Preprint Jul 2026

Agentic Bayesian Optimization through Surrogate-Augmented Autoresearch

This work introduces agentic Bayesian optimization: a paradigm in which an LLM agent is the central decision maker in the BO loop while a Bayesian backend provides the uncertainty-aware optimization substrate, and demonstrates the practical value of agentic BO in dynamic settings.

Paul Brunzema, Louis C. Tiao, Nhat Le et al. · 1 citation