To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision...
Abstract. This paper proposes an improved version of volume dominance to assign fitness to solutions in Pareto-based multi-objective optimisation. The impact of this revised volum...
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of combinatorial optimization problems. Some of the considered problems are tackled...
Benjamin Doerr, Anton Eremeev, Christian Horoba, F...
A model-free, case-based learning and control algorithm called S-learning is described as implemented in a simulation of a light-seeking mobile robot. S-learning demonstrated learn...
This paper presents a new approach for spatial event prediction that combines a value function approximation algorithm and case-based reasoning predictors. Each of these predictors...