基于多智能体和强化学习的优化算法

Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753) Pub Date : 2004-06-19 DOI:10.1109/CEC.2004.1330838

Yoko Kobayashi, E. Aiyoshi

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引用次数: 0

摘要

本文用多智能体算法(MAA)研究了排列类型的组合优化问题。为了提高优化能力，我们在该MAA中引入了强化学习和多个过程。通过对该算法在旅行商问题中的优化性能进行比较，结果表明该算法的优化效果优于传统的MAA算法和遗传算法。

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Optimization algorithm using multi-agents and reinforcement learning

This paper deals with combinatorial optimization of permutation type using multi-agents algorithm (MAA). In order to improve optimization capability, we introduced the reinforcement learning and several processes into this MAA. Optimization capability of this algorithm was compared in traveling salesman problem and it provided better optimization results than the conventional MAA and genetic algorithm.

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Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)

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