Matroid theory gives us powerful techniques for understanding combinatorial optimization problems and for designing polynomial-time algorithms. However, several natural matroid pr...
Several projects have developed compiler tools that translate high-level languages down to hardware description languages for mapping onto FPGAbased reconfigurable computers. Thes...
Dhananjay Kulkarni, Walid A. Najjar, Robert Rinker...
Abstract—In this paper, we propose a framework for employing opposition-based learning to assist evolutionary algorithms in solving discrete and combinatorial optimization proble...
We study the complexity of cost-optimal classical planning over propositional state variables and unary-effect actions. We discover novel problem fragments for which such optimiza...
Abstract— The role of gradient estimation in global optimization is investigated. The concept of a regional gradient is introduced as a tool for analyzing and comparing different...