Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
Abstract. We consider the line planning problem in public transportation, under a robustness perspective. We present a mechanism for robust line planning in the case of multiple li...
Apostolos Bessas, Spyros C. Kontogiannis, Christos...
Spoken utterance retrieval was largely studied in the last decades, with the purpose of indexing large audio databases or of detecting keywords in continuous speech streams. While...
Mickael Rouvier, Georges Linares, Benjamin Lecoute...
In this paper, we propose a novel adaptive step-size approach for policy gradient reinforcement learning. A new metric is defined for policy gradients that measures the effect of ...
Takamitsu Matsubara, Tetsuro Morimura, Jun Morimot...
In online tracking, the tracker evolves to reflect variations in object appearance and surroundings. This updating process is formulated as a supervised learning problem, thus a ...