Chapter

Ant Colony Optimization and Swarm Intelligence

Volume 4150 of the series Lecture Notes in Computer Science pp 506-507

Applying Aspects of Multi-robot Search to Particle Swarm Optimization

  • Jim PughAffiliated withSwarm-Intelligent Systems Group, École Polytechnique Fédérale de Lausanne
  • , Loïc SegapelliAffiliated withSwarm-Intelligent Systems Group, École Polytechnique Fédérale de Lausanne
  • , Alcherio MartinoliAffiliated withSwarm-Intelligent Systems Group, École Polytechnique Fédérale de Lausanne

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Abstract

Throughout the history of research, some of the most innovative and useful discoveries have arisen from a fusion of two or more seemingly unrelated fields of study; a characteristic of some method or process is enfused into a completely disjoint technique, and the resulting creation exhibits superior behavior. Some common examples include simulated annealing modeled after the annealing process in physics, Ant Colony Optimization modeled after the behavior of social insects, and the Particle Swarm Optimization algorithm modeled after the patterns of flocking birds.