动态编程原理用于逆向双倍随机递归的最佳控制问题和随机汉密尔顿-雅各比-贝尔曼方程的索波列夫弱解
Yunhong Li1, Anis Matoussi2, Lifeng Wei3,4
1Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China.
这项研究引入了一种新的逆向双随机递归最佳控制框架. 值函数被证明是唯一的索波列夫弱解,用于随机汉密尔顿-雅各比-贝尔曼方程.
科学领域:
- 随机分析 随机分析
- 最佳控制理论 最佳控制理论
- 部分微分方程 部分微分方程
背景情况:
- 逆向双随机微分方程 (BDSDE) 对于模拟具有前向和后向随机性的系统至关重要.
- 递归实用函数在金融和经济学中对于建模长期决策至关重要.
- 最佳控制问题涉及找到最好的策略来最大限度地减少或最大限度地减少给定的目标功能随着时间的推移.
研究的目的:
- 为了研究一个逆向的双倍随机递归的最佳控制问题.
- 为此类问题建立动态编程原理.
- 为了证明价值函数与随机汉密尔顿-雅各比-贝尔曼方程之间的联系.
主要方法:
- 使用逆向双倍随机微分方程,制定最佳控制问题.
- 开发和应用动态编程原则.
- 分析价值函数的属性作为索波列夫弱解.
主要成果:
- 呈现了动态编程原理,用于向后双随机递归的最佳控制.
- 值函数被证明是与之相关的随机汉密尔顿 - 雅各比 - 贝尔曼方程的独特索波列夫弱解.
- 这项工作为一类复杂的控制问题提供了严格的数学框架.
结论:
- 该研究成功地解决了一个具有挑战性的最佳控制问题,采用独特的成本函数配方.
- 这些发现为了解和解决各种应用中的这些问题提供了理论基础.
- 与随机汉密尔顿-雅各比-贝尔曼方程建立的联系为进一步的研究和数值方法开辟了道路.
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