Particle Swarm Optimization (PSO) is a new paradigm of Swarm Intelligence for optimization. Particle Swarm is a valuable tool to find optima in a fitness landscape, especially useful when dealing with a high number of dimensions and problems where problem specific information is non-existent. Its rapid convergence and small computational requirements make it a good candidate for solving optimization problems. This paradigm is inspired by concepts from Social Psychology and Artificial Life. It simulates social interactions among individuals, namely the emergence of social norms, and how they imitate behaviors of others of the same group that seem more successful than they are. The goal of this simulation is to have the individuals cooperate to find the global optimum of a fitness landscape.