Graphplan and heuristic state space planners such as HSP-R and UNPOP are currently two of the most effective approaches for solving classical planning problems. These approaches h...
The development of successful metaheuristic algorithms such as local search for a difficult problems such as satisfiability testing (SAT) is a challenging task. We investigate an ...
Heuristics are an increasingly popular solution method for combinatorial optimization problems. Heuristic use often frees the modeler from some of the restrictions placed on class...
In the last 25 years approximation algorithms for discrete optimization problems have been in the center of research in the fields of mathematical programming and computer science...
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...