A Regularized Nikaido-Isoda Function Approach to Multi-Leader-Follower Games
正则化Nikaido-Isoda函数方法求解多领导者-跟随者博弈
Atsushi Hori, Takayuki Okuno, Ellen H. Fukuda
AI总结 提出一种基于正则化Nikaido-Isoda函数的新重构方法,将多领导者-跟随者博弈近似为单层可微纳什均衡问题,避免高阶导数需求,适用于更广泛的博弈类。
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多领导者-跟随者博弈(MLFG)是一种层次非合作博弈,其中领导者在上层竞争,同时考虑下层跟随者的最优反应。求解MLFG的一种典型方法是通过将下层博弈替换为其KKT条件,将其重构为具有均衡约束的均衡问题(EPEC)。另一种方法,当每个跟随者的响应唯一时,是将MLFG重构为纳什均衡问题,将这些响应函数代入每个领导者的问题中。然而,这两种重构可能缺乏可扩展性,因为求解所得问题可能需要高阶导数。在本文中,我们通过利用正则化Nikaido-Isoda函数,并借助惩罚参数将MLFG近似为单层可微纳什均衡问题,提出了一种新的MLFG重构方法。所提出的重构既不需要跟随者博弈的导数信息,也不假设每个跟随者问题的凸性;因此,它可以处理更广泛的MLFG类。在全局子解析性条件下,我们分析了原始MLFG的均衡与所提重构之间的数学关系。
A multi-leader--follower game (MLFG) is a hierarchical noncooperative game in which leaders compete at the upper level while taking into account the followers' best responses at the lower level. A typical approach to solving the MLFG reformulates it as an equilibrium problem with equilibrium constraints (EPECs) by replacing the lower-level game with its KKT conditions. Another approach, when each follower's response is unique, is to reformulate the MLFG as a Nash equilibrium problem by substituting these response functions into each leader's problem. However, both reformulations may lack scalability since higher-order derivatives may be required when solving the resulting problems. In this paper, we propose a new reformulation of the MLFG by exploiting a regularized Nikaido--Isoda function and approximating the MLFG by a single-level differentiable Nash equilibrium problem with a penalty parameter. The proposed reformulation neither requires derivative information on the followers' game nor assumes convexity of each follower's problem; hence, it can handle a broader class of MLFGs. Under global subanalyticity, we analyze the mathematical relationship between equilibria of the original MLFG and the proposed reformulation.