We study the complexity of sequentially-optimal classical planning, and discover new problem classes for whose such optimization is tractable. The results are based on exploiting ...
Abstract. In constraint satisfaction, a general rule is to tackle the hardest part of a search problem first. In this paper, we introduce a parameter (τ) that measures the constr...
Scheduling decisions in time-critical systems are very difficult, due to the vast number of systems' parameters and tasks' attributes involved in such decisions. Due to ...
Influence maximization is the problem of finding a small subset of nodes (seed nodes) in a social network that could maximize the spread of influence. In this paper, we study the ...
Many machine learning tasks contain feature evaluation as one of its important components. This work is concerned with attribute estimation in the problems where class distribution...