  This paper describes the N-Tuple Bandit Evolutionary Algorithm (NTBEA), an
optimisation algorithm developed for noisy and expensive discrete
(combinatorial) optimisation problems. The algorithm is applied to two
game-based hyper-parameter optimisation problems. The N-Tuple system directly
models the statistics, approximating the fitness and number of evaluations of
each modelled combination of parameters. The model is simple, efficient and
informative. Results show that the NTBEA significantly outperforms grid search
and an estimation of distribution algorithm.
