一种基于粒计算的Multi-Agent决策算法

摘要

In order to improve the reliability of the decision-making and overcome the knowledge limitation of a single agent,this paper introduced an information fusion model based on evidence reasoning and granular computing,and defined the cooperative deci-sion-making of Multi-Agent. The decision making fusion has been divided into two stages of observing and decision-making. The obser-vation Agent takes feature vectors as inputs from environment information,and the result is that the information granulation method in-troduced in this paper can reduce the complexity of synthetic computation effectively.%为了克服单个Agent知识的局限性，提高系统决策的可靠性，提出了一种基于证据推理和粒计算的Multi-Agent决策信息融合算法，并对Multi-Agent合作决策进行了定义和描述。Multi-Agent决策融合划分为观测和决策两个阶段，观测Agent从环境信息中提取特征向量作为输入，信息粒化后降低了合成计算的复杂度。