Further results of Gravitational Swarm Intelligence for Graph Coloring

We provide enhanced results of an innovative nature inspired algorithm to solve the Graph Coloring Problem (GCP): the Gravitational Swarm Intelligence (GSI). Swarm Intelligence solves complex problems by extracting information from the spatial configurations of of agents that decide their actions/motions based on local available information, without any central control system. In the GSI application to GCP, agents correspond to graph´s nodes, moving as particles in the gravitatory field defined by some target objects corresponding to graph node colors. Knowledge of the graph´s topology is available to the agents´ local navigation control as friend-or-foe information. We discuss the convergence of the algorithm and test it over well-known benchmarking graphs, achieving good results in a reasonable time.