Many learning systems suffer from the utility problem; that is, that time after learning is greater than time before learning. Discovering how to assure that learned knowledge wil...
The study of transportability aims to identify conditions under which causal information learned from experiments can be reused in a different environment where only passive obser...
While techniques exist for simulating swarming behaviors, these methods usually provide only simplistic navigation and planning capabilities. In this review, we explore the benefi...
Abstract. This paper presents an endoscopic vision framework for modelbased 3D guidance of surgical instruments used in robotized laparoscopic surgery. In order to develop such a s...
Christophe Doignon, Florent Nageotte, Michel de Ma...
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...