进化建模和网络动态游戏的控制与事件触发机制
Xiangyong Chen1,2, Jun-E Feng2, Wenying Xu3
1School of Automation and Electrical Engineering, Linyi University, Linyi 276005, China.
Chaos (Woodbury, N.Y.)
|January 3, 2025
概括
本研究介绍了事件动态游戏 (EDG),用于模拟智能代理之间的离散事件决策. 它开发了新的状态空间和网络演变模型,以分析游戏动态和合作行为.
科学领域:
- 人工智能的人工智能
- 游戏理论 游戏理论
- 网络科学 网络科学
背景情况:
- 在具有多个智能代理的动态环境中做出决策会带来复杂的挑战.
- 现有的模型可能无法完全捕捉相互作用的时间和战略演变.
研究的目的:
- 引入和分析事件动态游戏 (EDG),用于离散事件决策.
- 为EDG开发新的状态空间和网络演变模型.
- 调查EDG内部的平衡解决方案和时间演变行为.
主要方法:
- 为EDG开发一种新的状态空间模型.
- 应用网络演变原则来建模EDG网络.
- 使用正常形式的战略方法建立游戏树演化模型.
- 分析多层次的时间演变和合作节点行为.
主要成果:
- 为EDG引入一种新的状态空间模型,分析平衡存在.
- 开发一个游戏树进化模型,扩展战略表达.
- 创建一个网络演变模型来分析时间动态和合作行为.
- 通过应用示例验证拟议的模型.
结论:
- 拟议的模型有效地捕捉了非合作环境中的离散事件动态决策过程.
- 该框架提供了关于动态游戏网络中策略和合作行为的演变的见解.
- 该研究提供了一种强大的方法来分析多代理系统中的复杂相互作用.
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