相关实验视频
Updated: Jun 23, 2025

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The HoneyComb Paradigm for Research on Collective Human Behavior
Published on: January 19, 2019
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分布纳什平衡在非合作性游戏中寻找邻居的部分决策信息
Xin Jin1, Kaihong Lu2, Zhengxin Wang3
1School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China.
Chaos (Woodbury, N.Y.)
|June 25, 2024
概括
这项研究旨在在复杂网络中找到纳什平衡,在复杂网络中,参与者拥有不完整的信息. 它开发了一个双层模型,以在行动上达成共识并达到平衡,即使有网络变化.
科学领域:
- 游戏理论 游戏理论
- 网络科学 网络科学
- 分布式系统 分布式系统
背景情况:
- 在现实世界的场景中,玩家通常会因为竞争而隐信息.
- 在具有部分信息的复杂网络中找到分布式纳什平衡是具有挑战性的.
研究的目的:
- 调查分布式纳什平衡寻找与部分邻居信息.
- 在非合作游戏中制定共识和趋同到平衡的模型.
主要方法:
- 为游戏互动和动作估计构建了一个双层网络模型.
- 采用了利亚普诺夫函数方法和拉萨尔不变原理.
- 用于切换拓的平均停留时间方法.
主要成果:
- 在个别行动和估计方面达成共识.
- 保证的人口行动汇聚到纳什平衡点.
- 根据固定和交换拓学的收条件衍生.
结论:
- 提出的方法提供了足够的条件,以实现纳什平衡在分布式非合作游戏与部分信息.
- 理论结果通过固定和开关网络拓学的数值示例来验证.
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