Watch thy neighbor or how the swarm can learn from its environment

摘要

Particle swarm optimization is a novel algorithm where a population of candidate problem solution vectors evolves "social" norms by being influenced by their topological neighbors. Until now, an individual was influenced by its best performance acquired in the past and the best experience observed in its neighborhood. In this paper, we introduce new ways an individual can be influenced by its neighbors.