基于信息融合的MAS协同方法及其在RoboCupRescue仿真系统中的应用

Min Wu, Xiaoyong Zhang, Jun Peng, Kuo-Chi Lin
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引用次数: 0

摘要

协作是多智能体系统的关键问题之一。提出了一种基于信息融合概念的多智能体协作方法,该方法可以快速划分任务,避免任务重叠和资源冲突。在该模型中,我们将智能体分为两类:传感器智能体和决策智能体。具有感知和动作能力的传感器智能体将原始的传感器信息转换成确定的协议并传递给决策智能体。决策智能体采用基于动态贝叶斯网络的方法,从大量的传感器信息中推断出决策可靠的态势评估,然后检索出一个最佳动作集,发送给传感器智能体执行。该模型在RoboCupRescue仿真比赛中得到了有效的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A collaboration method of MAS based on information fusion and its application in RoboCupRescue simulation system
Collaboration is one of the key issues in multi-agent system. This paper presents a multi-agent collaboration method based on the concept of information fusion in which the tasks can be divided quickly without task overlapping and resource conflicting. In this model we classify the agents into two categories: sensor agents and decision agents. Sensor agents with the abilities of sensing and action convert the raw sensor information into a definite protocol and transmit them to decision agents. Decision agents adopt a method based on dynamic Bayesian networks to infer the situation assessment which is reliable for decision making from large quantities of sensor information, and then retrieve a best action set which will be sent to sensor agents to execute. This model has applied effectively in RoboCupRescue simulation competition.
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