Organizational Behavior Management System Based on Multi-Agent Algorithm

Zhiru Wei
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Abstract

Self-organizing multi-agent system theory can be easily used to solve some complex problems that are still difficult to solve by combining the advantages and characteristics of self-organizing theory and multi-agent system theory. The purpose of this paper is based on Multi-Agent Algorithm Research Organizational Behavior Management System. Aiming at the problem that the existing multi-Agent-based organizational behavior management system has less application and implementation platforms, an organizational behavior management system based on multi-Agent algorithm is planned and implemented. The system configuration is centered on the multi-agent interaction subsystem and the vehicle behavior management subsystem, and the vehicle behavior management service is performed through the environment recognition input control system. The two organizational behavior management programs, AOM and OMACS, were tested. The results showed that when the number of Agents was 8, the average task completion quality AQ of the AOM organizational program was 106. The system has good efficiency and strong adaptability to complex real-time control environment.
基于多agent算法的组织行为管理系统
自组织多智能体系统理论结合了自组织理论和多智能体系统理论的优点和特点,可以很容易地解决一些目前还难以解决的复杂问题。本文的目的是研究基于多智能体算法的组织行为管理系统。针对现有基于多agent的组织行为管理系统应用和实现平台少的问题,设计并实现了一种基于多agent算法的组织行为管理系统。系统配置以多智能体交互子系统和车辆行为管理子系统为中心,通过环境识别输入控制系统实现车辆行为管理服务。对AOM和OMACS两种组织行为管理程序进行了测试。结果表明,当agent数为8时,AOM组织方案的平均任务完成质量AQ为106。该系统效率高,对复杂的实时控制环境适应性强。
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