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The Cartographer
Evolving Order and Chaos: Comparing Particle Swarm Optimization and Genetic Algorithms for Global Coordination of Cellular Automata
September 08, 2019 Β· Declared Dead Β· π IEEE Congress on Evolutionary Computation
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Authors
Anthony D. Rhodes
arXiv ID
1909.03560
Category
cs.AI: Artificial Intelligence
Cross-listed
cs.NE
Citations
0
Venue
IEEE Congress on Evolutionary Computation
Last Checked
4 months ago
Abstract
We apply two evolutionary search algorithms: Particle Swarm Optimization (PSO) and Genetic Algorithms (GAs) to the design of Cellular Automata (CA) that can perform computational tasks requiring global coordination. In particular, we compare search efficiency for PSO and GAs applied to both the density classification problem and to the novel generation of 'chaotic' CA. Our work furthermore introduces a new variant of PSO, the Binary Global-Local PSO (BGL-PSO).
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