—We develop a stochastic local search algorithm for finding Pareto points for multi-criteria optimization problems. The algorithm alternates between different single-criterium o...
—Despite the range of applications and successes of evolutionary algorithms, expensive fitness computations often form a critical performance bottleneck. A preferred method of r...
— The aim of this paper is to introduce the use of Tower Defence (TD) games in Computational Intelligence (CI) research. We show how TD games can provide an important test-bed fo...
Phillipa Avery, Julian Togelius, Elvis Alistar, Ro...
Abstract—In this paper, we propose a framework for employing opposition-based learning to assist evolutionary algorithms in solving discrete and combinatorial optimization proble...