基于多智能体的粒子群优化方法

2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems Pub Date : 2007-06-11 DOI:10.1109/KIMAS.2007.369820

R. Ahmad, Yung-Chuan Lee, S. Rahimi, B. Gupta

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引用次数: 24

摘要

提出了一种新的粒子群优化方法——基于agent的粒子群优化算法。通过赋予粒子更多的自主权、异步执行和卓越的学习能力，群体被提升到多智能体系统的地位。问题空间被建模为一个环境，它形成了已知非最优点的簇，这将环境转化为一个更动态和信息丰富的资源

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A Multi-Agent Based Approach for Particle Swarm Optimization

We propose a new approach towards particle swarm optimization named agent-based PSO. The swarm is elevated to the status of a multi-agent system by giving the particles more autonomy, an asynchronous execution, and superior learning capabilities. The problem space is modeled as an environment which forms clusters of points that are known to be non-optimal and this transforms the environment into a more dynamic and informative resource

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2007 International Conference on Integration of Knowledge Intensive Multi-Agent Systems

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