Abstract. The application of reinforcement learning algorithms to multiagent domains may cause complex non-convergent dynamics. The replicator dynamics, commonly used in evolutiona...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Fa...
Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
Abstract. This paper proposes a fast method for dense 3-D interpretation to directly estimate a dense map of relative depth and motion from a monocular sequence of images on large ...
Abstract. Opposing the pre-dominant turn-wise statistics of acoustic LowLevel-Descriptors followed by static classification we re-investigate dynamic modeling directly on the frame...
Abstract. Choosing a good variable order is crucial for making symbolic state-space generation algorithms truly efficient. One such algorithm is the MDD-based Saturation algorithm ...