Constraint Programming is an attractive approach for solving AI planning problems by modelling them as Constraint Satisfaction Problems (CSPs). However, formulating effective cons...
Andrea Rendl, Ian Miguel, Ian P. Gent, Peter Grego...
Domain filtering local consistencies, such as inverse consistencies, that only delete values and do not add new constraints are particularly useful in Constraint Programming. Alt...
—In this paper, we consider multi-hop wireless mesh networks, where each router node is equipped with multiple radio interfaces and multiple channels are available for communicat...
: SimStudent is a machine-learning agent that learns cognitive skills by demonstration. It was originally developed as a building block of the Cognitive Tutor Authoring Tools (CTAT...
Noboru Matsuda, William W. Cohen, Jonathan Sewall,...
This paper presents results toward our ongoing research program into hands-off assistive human-robot interaction [6]. Our work has focused on applications of socially assistive r...