As robots become a mass consumer product, they will need to learn new skills by interacting with typical human users. Past approaches have adapted reinforcement learning (RL) to a...
Local search algorithms often get trapped in local optima. Algorithms such as tabu search and simulated annealing 'escape' local optima by accepting nonimproving moves. ...
Laura Barbulescu, Jean-Paul Watson, L. Darrell Whi...
The bias-variance decomposition is a very useful and widely-used tool for understanding machine-learning algorithms. It was originally developed for squared loss. In recent years,...
A variety of reactive plan execution systems have been developed in recent years, each attempting to solve the problem of taking reasonable courses of action fast enough in a dyna...
In this paper we present the results of our user study about status message sharing on the Social Web. The study revealed the privacy and information noise (sometimes originating f...
Milan Stankovic, Alexandre Passant, Philippe Laubl...