方法证据记录
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Agent-Based Ant Colony Optimization
分类方法记录 · 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
精选声明
声明已持久化到证据分类账中,每个声明都有自己的评估。
尚无精选声明
当分类账中没有声明时,此视图不会自行创建声明评估。
相关方法
从方法图中生成,显示为机器建议的关系 — 不推断任何证据声明。