Applying Swarm IntelligenceNature is amazing and it provides inspiration for computer scientists in the most distinct ways. Swarm intelligence is a good example of this. As Gestalt psychologist Kurt Koffka once said, “The whole is other than the sum of the parts”. Swarm intelligence goes along the same line of thinking; it is linked to group intelligence behavior, how smart the collective behavior is and how the behavior of each individual member contributes to the whole. Sometimes, the synergy between members of one group, e.g. the collective behaviors of social insects such as ants and bees, presents an intelligence that goes far beyond the intelligence of each of its members. Some researchers even consider the collective, the swarm, as one single and unique individual. This individual can perform actions, or exhibit a behavior, that the individual members of the group alone would not be able to do. The main characteristic of swarm intelligence algorithms is that they automatically evolve by stimulating the social behavior of organisms. By sharing information and taking the information of others into account, the behavior of the individuals is optimized to achieve a certain objective, which is normally much higher than the individual actions of the members of the group.