We benchmark an independent-restart-(1+1)-CMA-ES on the BBOB-2009 noisy testbed. The (1+1)-CMA-ES is an adaptive stochastic algorithm for the optimization of objective functions d...
The BFGS quasi-Newton method is benchmarked on the noisy BBOB-2009 testbed. A multistart strategy is applied with a maximum number of function evaluations of about 104 times the s...
This paper describes Pairwise Bisection: a nonparametric approach to optimizing a noisy function with few function evaluations. The algorithm uses nonparametric reasoning about si...
—This paper introduces an algorithm for direct search of control policies in continuous-state discrete-action Markov decision processes. The algorithm looks for the best closed-l...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
The (1+1)-ES with one-fifth success rule is one of the first and simplest stochastic algorithm proposed for optimization on a continuous search space in a black-box scenario. In...