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We present a modified version of the Particle swarm Optimization algorithm in which we adjust the virtual swarm search by incorporating inter-agent dynamics native to multi-robot search scenarios. The neighborhood structure of PSO is modified to accurately represent feasible neighborhoods in multiple robot systems with limited communication in several different ways. The new algorithms are tested on several standard benchmark problems with a varying number of dimensions and are shown to offer superior performances to the standard algorithm in some cases. Further potential modifications and uses of the new algorithms are discussed.