where D is the number of dimensions, x ∈ [-1, 1] D , and the minimum appears at x * = (-0.85297) D . The experiment starts with a single random point (the same starting point is chosen for each algorithm) and includes 50 iterations for each method. For Bayesian optimisation, Gaussian processes and lower confidence bound were used as the surrogate