机器人世界杯救援仿真系统中简单蚁群优化agent动作获取方法的介绍

2011 Third International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2011-11-30 DOI:10.1109/INCoS.2011.105

Hisayuki Sasaoka

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引用次数: 0

摘要

提出了一种基于蚁群算法的多智能体系统中智能体动作获取方法。蚁群算法是一种强大的元启发式算法，一些研究人员已经报道了该算法在一些应用中的有效性[1-4]。在机器人世界杯救援模拟系统中，利用所提出的方法开发了消防队员。本研究的最终目标是实现多智能体系统中不同智能体之间的协作。而本次针对我所在团队的消防队员实施的研究就是实现这一目标的第一步。

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Introduction of Acquiring Method for Agents' Actions with Simple Ant Colony Optimization in RoboCup Rescue Simulation System

This paper has presented acquiring method for agents' actions using Ant Colony Optimization (ACO) in multi-agent system. ACO is one of powerful meta-heuristics algorithms and some researchers have reported the effectiveness of some applications with the algorithm [1-4]. I have developed fire brigade agents using proposed method in RoboCup rescue simulation system. The final goal of this research is an achievement of co-operations for hetero-agent in multi-agent systems. Then this research for implementation for fire brigade agents in my team is the first step of this goal.

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2011 Third International Conference on Intelligent Networking and Collaborative Systems

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