A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. It is commonly asserted that in order to ...
Sample selection bias is a common problem in many real world applications, where training data are obtained under realistic constraints that make them follow a different distribut...
Among the most important challenges for contemporary AI research are the development of methods for improved robustness, adaptability, and overall interactiveness of systems. Inter...
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
Modern scientific collaborations have opened up the opportunity of solving complex problems that involve multidisciplinary expertise and large-scale computational experiments. The...
Chee Sun Liew, Malcolm P. Atkinson, Jano I. van He...