Researchers who make tutoring systems would like to know which sequences of educational content lead to the most effective learning by their students. The majority of data collecte...
In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from sce...
In this paper, we present a dynamic and adaptive variable ordering heuristic which guides systematic search toward inconsistent or hard parts of a Constraint Satisfaction Problem (...
We use large deviations to prove a general theorem on the asymptotic edge-weighted height Hn of a large class of random trees for which Hn c log n for some positive constant c. A...
A hybrid algorithm is devised to boost the performance of complete search on under-constrained problems. We suggest to use random variable selection in combination with restarts, ...