In this work we explore how the complexity of a problem domain affects the performance of evolutionary search using a performance-based restart policy. Previous research indicates...
Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent,...
Stefan Mutter, Bernhard Pfahringer, Geoffrey Holme...
Abstract. Two approaches have been used to perform approximate inference in Bayesian networks for which exact inference is infeasible: employing an approximation algorithm, or appr...
LPG is a planner that performed very well in the last International planning competition (2002). The system is based on a stochastic local search procedure, and it incorporates se...
In this paper we test whether a correlation exists between the optimal mutation rate and problem difficulty. We find that the range of optimal mutation rates is inversely proporti...