Abstract: Testing controllers in safety-critical systems is vital for ensuring their safety and preventing catastrophic failures. In this paper, we address the falsification problem within closed-loop ...

PyBADS is a Python implementation of the Bayesian Adaptive Direct Search (BADS) algorithm for solving difficult and mildly expensive optimization problems, originally implemented in MATLAB. BADS has ...

The growing demand for innovative research in the food industry is driving the adoption of robots in large-scale experimentation, a shift that offers increased precision, repeatability, and efficiency ...

SMAC offers a robust and flexible framework for Bayesian Optimization to support users in determining well-performing hyperparameter configurations for their (Machine Learning) algorithms, datasets ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

Abstract: This paper introduces CausalBO, a Python package developed to enhance the applicability and utility of the Causal Bayesian Optimization (CBO) algorithm. The original CBO algorithm, developed ...

The total budget of a breeding program must be divided across its different parts to maximize gain. How to achieve optimal budget allocations for a two-part strategy breeding scheme is an unsolved ...