分布纳什平衡 寻找多集群 欧勒 - 拉格朗日系统的聚合游戏,具有合约束
IEEE transactions on cybernetics
|January 18, 2024
概括
本研究介绍了分布式纳什平衡在复杂的多集群游戏中寻找具有不确定的动态的新适应策略. 该方法确保玩家在各种约束的情况下准确地趋于通用纳什平衡 (GNE).
科学领域:
- 控制系统工程 控制系统工程
- 游戏理论 游戏理论
- 优化优化 优化优化
背景情况:
- 分布纳什平衡的寻求对于多代理系统至关重要.
- 聚合游戏涉及复杂的相互依赖和约束.
- 不确定的欧勒-拉格朗日 (EL) 动态在控制方面带来了重大挑战.
研究的目的:
- 开发一种分布式策略,在多集群聚合游戏中寻求通用纳什平衡 (GNE).
- 解决局部设置,集群内部共识和集群内部合约束的问题.
- 在播放器模型中处理不确定的欧勒-拉格朗日 (EL) 动态.
主要方法:
- 提出了一个自适应的连续时间分布式策略.
- 一个使用投影,梯度下降和动态平均共识的新型辅助系统被合成.
- 为具有不确定的参数的EL系统开发了自适应跟踪算法.
主要成果:
- 开发的战略实现了与GNE的准确趋同.
- 利亚普诺夫的稳定理论证实了该战略的有效性.
- 数字模拟验证了理论发现.
结论:
- 拟议的自适应分布式策略有效地解决了多集群聚合游戏与不确定的EL动态的GNE寻找问题.
- 该方法成功地处理复杂的约束场景.
- 这项工作有助于在多代理系统中实现强大的分布式优化和控制.
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