Correlated equilibria arise naturally when agents communicate or rely on intermediaries such as recommendation systems. We study when a given Nash equilibrium can be improved within the set of correlated equilibria for general objectives. Our key insight is a detail-free criterion: any Nash equilibrium with three or more randomizing agents is generically improvable. We refine this insight to specific classes of games and objectives, including Pareto and utilitarian welfare, and provide constructive methods to obtain improvements. Our findings underscore the ubiquity of improvable Nash equilibria and the crucial role of correlation in enhancing strategic outcomes.

翻译：关联均衡在智能体相互沟通或依赖推荐系统等中介时自然出现。我们研究了一般目标下，在关联均衡集合中特定纳什均衡何时可被改进。我们的关键洞见是一个无细节标准：任何包含三个及以上随机化智能体的纳什均衡皆具有可改进的普适性。我们将这一洞见细化到特定博弈类别与目标（包括帕累托最优与功利主义福利），并提供了获取改进的构造性方法。研究结果凸显了可改进纳什均衡的普遍性，以及关联性在增强策略结果中的关键作用。