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Implementation of Ant Colony Algorithm Based-On Multi-agent System

机译:基于多智能体系统的蚁群算法的实现

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摘要

Ant colony algorithm (ACA) is a simulated evolutionary algorithm which was developed in recent years. ACA has attracted many researchers' attentions for the solving of combinatorial optimization problems. Agent-based simulation (ABS) is one of novel methods for the analysis of complex system. This paper introduces the basic principles of ACA and its method of design and implement in a multi-agent system (MAS). Computer simulation results of MAS based on ACA are introduced and discussed in this thesis. The results show that the reasonable combination of ACA and the simple local rules of agent can effectively improve the colony behaviors of agents.
机译:蚁群算法(ACA)是近年来发展起来的一种模拟进化算法。 ACA解决组合优化问题吸引了许多研究人员的关注。基于代理的仿真(ABS)是用于分析复杂系统的新颖方法之一。本文介绍了ACA的基本原理及其在多主体系统(MAS)中的设计和实现方法。本文介绍并讨论了基于ACA的MAS计算机仿真结果。结果表明,ACA与简单的代理局部规则的合理组合可以有效改善代理的菌落行为。

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