Surface fitting refers to the process of constructing a smooth representation for an object surface from a fairly large number of measured 3D data points. This paper presents an ...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Modeling self-adaptive applications is a difficult task due to the complex relationships they have with their environments. Designers of such applications strive to model accurate...
This paper proposes a new planning architecture for agents operating in uncertain and dynamic environments. Decisiontheoretic planning has been recognized as a useful tool for rea...