The particle swarm: social adaptation of knowledge
Top Cited Papers
- 22 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 303-308
- https://doi.org/10.1109/icec.1997.592326
Abstract
Particle swarm adaptation is an optimization paradigm that simulates the ability of human societies to process knowledge. The algorithm models the exploration of a problem space by a population of individuals; individuals' successes influence their searches and those of their peers. The algorithm is relevant to cognition, in particular the representation of schematic knowledge in neural networks. Particle swarm optimization successfully optimizes network weights, simulating the adaptive sharing of representations among social collaborators. The paper introduces the algorithm, begins to develop a social science context for it, and explores some aspects of its functioning.Keywords
This publication has 7 references indexed in Scilit:
- Particle swarm optimizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Parallel Distributed ProcessingPublished by MIT Press ,1986
- Vicarious Processes: A Case of No-Trial LearningAdvances in Experimental Social Psychology, 1965
- A Theory of Cognitive DissonancePublished by Walter de Gruyter GmbH ,1957
- Some effects of certain communication patterns on group performance.The Journal of Abnormal and Social Psychology, 1951
- Knowledge and purpose as habit mechanisms.Psychological Review, 1930
- Animal intelligence; experimental studiesPublished by Biodiversity Heritage Library ,1911