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引用次数: 0
摘要
完美均衡的概念由塞尔滕(Int J Game Theory 4:25-55, 1975)提出,是策略扰动中理性的有效表征。在我们的研究中,我们提出了一个包含扰动控制参数的修正版完全均衡。为了使信念与均衡选择概率相匹配,McKelvey 和 Palfrey(Games Econ Behav 10:6-38, 1995)建立了逻辑量子响应均衡(logistic QRE),它只能选择纳什均衡。通过引入混合策略剖面与给定正元素向量之间的线性组合,本文开发了一种用于选择完美均衡特殊版本的逻辑 QRE 变体。在这一变体的基础上,我们构建了一个包含额外变量指数函数的均衡系统。通过严格的误差约束分析,我们证明了当额外变量趋近于零时,该均衡系统的解集会导致完美均衡。因此,我们确定了通向完全均衡的平滑路径的存在,并采用了变量的指数变换来确保数值稳定性。为了进行数值比较,我们利用了平方根 QRE 的一个变体,它产生了另一条通向完全均衡的平滑路径。数值结果进一步验证了所提出的可微分路径跟踪方法的有效性和效率。
A Variant of the Logistic Quantal Response Equilibrium to Select a Perfect Equilibrium
The concept of perfect equilibrium, formulated by Selten (Int J Game Theory 4:25–55, 1975), serves as an effective characterization of rationality in strategy perturbation. In our study, we propose a modified version of perfect equilibrium that incorporates perturbation control parameters. To match the beliefs with the equilibrium choice probabilities, the logistic quantal response equilibrium (logistic QRE) was established by McKelvey and Palfrey (Games Econ Behav 10:6–38, 1995), which is only able to select a Nash equilibrium. By introducing a linear combination between a mixed strategy profile and a given vector with positive elements, this paper develops a variant of the logistic QRE for the selection of the special version of perfect equilibrium. Expanding upon this variant, we construct an equilibrium system that incorporates an exponential function of an extra variable. Through rigorous error-bound analysis, we demonstrate that the solution set of this equilibrium system leads to a perfect equilibrium as the extra variable approaches zero. Consequently, we establish the existence of a smooth path to a perfect equilibrium and employ an exponential transformation of variables to ensure numerical stability. To make a numerical comparison, we capitalize on a variant of the square-root QRE, which yields another smooth path to a perfect equilibrium. Numerical results further verify the effectiveness and efficiency of the proposed differentiable path-following methods.
期刊介绍:
The Journal of Optimization Theory and Applications is devoted to the publication of carefully selected regular papers, invited papers, survey papers, technical notes, book notices, and forums that cover mathematical optimization techniques and their applications to science and engineering. Typical theoretical areas include linear, nonlinear, mathematical, and dynamic programming. Among the areas of application covered are mathematical economics, mathematical physics and biology, and aerospace, chemical, civil, electrical, and mechanical engineering.