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Agent-based ant colony optimization

Agent-Based Ant Colony Optimization (AB-ACO) models individual ants as autonomous agents that probabilistically construct solutions by following and depositing pheromone trails on a search graph. By coupling agent-level behavioral rules with a shared pheromone environment, the collective system converges on high-quality solutions to hard combinatorial and simulation-embedded optimization problems without central coordination.

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Agent-Based Ant Colony Optimization

Taksonoomiline meetodikirje · process-pipeline / simulation

Dorigo, M., Stutzle, T. (2004). Ant Colony Optimization. MIT Press, Cambridge, MA. · ISBN 9780262042192
Bonabeau, E., Dorigo, M., Theraulaz, G. (1999). Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York. · ISBN 9780195131581

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Same method familyAgent-Based Modelingmachine-suggested · Relational suggestion, not evidence.Same method familyAnt Colony Optimizationmachine-suggested · Relational suggestion, not evidence.Same method familyGenetic Algorithmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMulti-objective ant colony optimizationmachine-suggested · Relational suggestion, not evidence.Same method familyParticle Swarm Optimizationmachine-suggested · Relational suggestion, not evidence.