One of the original motivations for research in qualitative physics was the development of intelligent tutoring systems and learning environments for physical domains and complex ...
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...
In previous work, we proposed a unique landmark-based map learning method for mobile robots based on the “co-visibility” information i.e., very coarse qualitative information o...
A typical goal for transfer learning algorithms is to utilize knowledge gained in a source task to learn a target task faster. Recently introduced transfer methods in reinforcemen...
Transfer learning problems are typically framed as leveraging knowledge learned on a source task to improve learning on a related, but different, target task. Current transfer met...