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Necessary/sufficient conditions for Pareto optimality in finite horizon mean-field type stochastic differential game

机译:有限地平线平均场型随机差动游戏中帕累托最优性的必要/充分条件

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摘要

This paper is concerned with necessary and sufficient conditions for the existence of Pareto solutions in finite horizon mean-field type stochastic cooperative differential game. Based on the equivalent characterization of Pareto optimality, the problem is transformed into a set of constrained mean-field type stochastic optimal control problems with a special structure. Utilizing the mean-field type stochastic minimum principle, the necessary conditions are put forward. Under certain convex assumptions, it is shown that the necessary conditions are also sufficient ones. Next, the indefinite linear quadratic (LQ) case is studied. It is pointed out that the solvability of two related generalized differential Riccati equations (GDREs) provides a sufficient condition under which Pareto efficient strategies are equivalent to weighted sum optimal controls. In addition, all Pareto solutions are obtained based on the solutions of two generalized differential Lyapunov equations (GDLEs). At last, an example sheds light on the effectiveness of the theoretical results. (C) 2020 Published by Elsevier Ltd.
机译:本文涉及有限地平线平均场型随机协同差异游戏中帕累托解决方案的必要和充分条件。基于Pareto最优性的等效表征,问题被转换为具有特殊结构的一组约束平均场型随机最佳控制问题。利用平均场型随机最小原理,提出了必要的条件。在某些凸起假设下,表明必要条件也是足够的。接下来,研究了无限线性二次(LQ)案例。指出,两个相关的广义差分Riccati等式(GDRES)的可解性提供了足够的条件,帕累托有效的策略等同于加权和最佳控制。此外,基于两个广义差分Lyapunov方程(GDLE)的溶液获得所有帕累托解决方案。最后,一个例子揭示了理论结果的有效性。 (c)2020年由elestvier有限公司发布

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