Transfer learning has proven to be a wildly successful approach for speeding up reinforcement learning. Techniques often use low-level information obtained in the source task to a...
Tim Brys, Anna Harutyunyan, Matthew E. Taylor, Ann...
Consider a good (such as a hotel room) which, if not sold on time, is worth nothing to the seller. For a customer who is considering a choice of such goods, their prices may chang...
Partially observable Markov decision processes (POMDPs) provide a natural framework to design applications that continuously make decisions based on noisy sensor measurements. The...
In this work we propose a decision-theoretic approach to Intelligent Tutoring Systems (ITSs) that seeks to alleviate the need for extensive development and hand-tuning in the desi...