Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
We introduce a master–worker framework for parallel global optimization of computationally expensive functions using response surface models. In particular, we parallelize two r...
Background: Popular methods to reconstruct molecular phylogenies are based on multiple sequence alignments, in which addition or removal of data may change the resulting tree topo...
Olivier Bastien, Philippe Ortet, Sylvaine Roy, Eri...
Abstract. Real-world optimization problems are often subject to uncertainties, which can arise regarding stochastic model parameters, objective functions and decision variables. Th...
Background: Pseudogenes, nonfunctional copies of genes, evolve fast due the lack of evolutionary pressures and thus appear in several different forms. PseudoGeneQuest is an online...