Abstract. Learning in the context of constraint solving is a technique by which previously unknown constraints are uncovered during search and used to speed up subsequent search. R...
Ian P. Gent, Christopher Jefferson, Lars Kotthoff,...
Based in part on observations about the incremental nature of most state changes in biological systems, we introduce the idea of Memory with Memory in Genetic Programming (GP), wh...
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder, Michael Kirley, Ra...
The goal of testing is to discriminate between multiple hypotheses about a system--for example, different fault diagnoses--by applying input patterns and verifying or falsifying t...