Designing a computer-supported learning scenario involving a constructivist approach of learning lays on a paradox. On the one hand, learning flows must be precisely described –...
Anne Lejeune, Muriel Ney, Armin Weinberger, Margus...
This work proposes concepts, designs, experiences and lessons learned from some studies of ad hoc learning supported by wireless and mobile technologies. The ad hoc learning activi...
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
We present the first large-scale empirical application of reinforcement learning to the important problem of optimized trade execution in modern financial markets. Our experiments...
A fast-growing body of research in the AI and machine learning communities addresses learning in games, where there are multiple learners with different interests. This research a...