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在多剂系统中提取前沿边界剂的新方法
Fengying Yang1,2, Zia Ur Rehman3, Ahmad Din4
1School of Computer and Artificial Intelligence, Huanghuai University, No. 76 Kaiyuan Avenue, Zhumadian, 463000, Henan, China. happyay2008@126.com.
Scientific reports
|December 1, 2025
概括
本研究介绍了前边界代理在多代理系统中的决策. 快速前沿边界检测 (FFBD) 算法准确地识别这些代理,优于上凸船体 (UCH) 算法.
科学领域:
- 人工智能的人工智能
- 复杂的系统复杂的系统.
- 拓学的拓学
背景情况:
- 分布式多代理系统需要有效的决策机制.
- 生物群中的集体行为激发了代理协调的模型.
- 像边界集这样的拓概念为定义代理角色提供了框架.
研究的目的:
- 引入并正式定义前沿边界代理人的概念.
- 在不确定的环境条件下开发用于识别前沿边界代理的算法.
- 评估和比较拟议的算法与人类判断的性能.
主要方法:
- 前边界代理模型的正式定义.
- 开发了两个算法:上凸船体 (UCH) 和快速前沿边界检测 (FFBD).
- 在常规和随机集群上进行模拟实验,随后与人类参与者进行问卷调查.
主要成果:
- 快速前线边界检测 (FFBD) 算法与"多数规则"原则保持一致.
- 与UCH算法相比,FFBD显示出更高的准确性和稳定性.
- 评估指标 (合适度,豪斯多夫距离,平均值推导) 证实了FFBD的有效性.
结论:
- 该FFBD算法是一种强大的方法,用于识别分布式系统的前边界代理.
- 该研究验证了在集体行为分析中对人类知觉的算法方法.
- 这些发现有助于提高人工多代理系统的决策能力.
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