0000000000146443

AUTHOR

Nathan Bell

showing 2 related works from this author

Particle Field Optimization: A New Paradigm for Swarm Intelligence

2015

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A novel abstraction for swarm intelligence: particle field optimization

2016

Particle swarm optimization (PSO) is a popular meta-heuristic for black-box optimization. In essence, within this paradigm, the system is fully defined by a swarm of "particles" each characterized by a set of features such as its position, velocity and acceleration. The consequent optimized global best solution is obtained by comparing the personal best solutions of the entire swarm. Many variations and extensions of PSO have been developed since its creation in 1995, and the algorithm remains a popular topic of research. In this work we submit a new, abstracted perspective of the PSO system, where we attempt to move away from the swarm of individual particles, but rather characterize each …

Mathematical optimizationMeta-optimizationbusiness.industryComputer scienceComputingMethodologies_MISCELLANEOUSComputer Science::Neural and Evolutionary ComputationParticle swarm optimizationSwarm behaviour02 engineering and technology010502 geochemistry & geophysics01 natural sciencesSwarm intelligenceField (computer science)Artificial Intelligence0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligenceMulti-swarm optimizationbusinessMetaheuristic0105 earth and related environmental sciencesAbstraction (linguistics)Autonomous Agents and Multi-Agent Systems
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