竞争性中介博弈与城市自动驾驶车辆（CAV）路径规划市场
Competitive mediator games and urban CAV routing markets
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中文总结 AI 辅助
本文针对未来自动驾驶路径规划与驾驶市场，提出竞争性中介博弈，证明特定条件下其均衡为垄断，并探讨相关市场的机制设计问题。
中文摘要 AI 辅助
受未来自动驾驶路径规划与驾驶（ARAD）市场的启发，本文引入竞争性中介博弈及其均衡，该均衡是（粗糙）相关均衡的推广。近年来，（粗糙）相关均衡成为热门研究领域，因其不仅可能比纳什均衡更具社会效率，还是算法无遗憾多智能体学习动态的极限。本文讨论了竞争性中介博弈的基本性质，并证明：在匿名拥塞（路径规划）博弈的通用设定中，当中介以市场份额最大化为目标，且所有用户都至少偏好某一个中介弱于其他中介时，所有竞争性中介均衡均为垄断。本文将这些结果应用于竞争性ARAD服务提供商的新市场背景并进行解读，还对这些市场进行了全面概述，探讨了其未来机制设计方向。
英文摘要
Inspired by possible future markets of autonomous routing and driving (ARAD), we introduce competitive mediator games and their equilibria which generalize the (coarse) correlated equilibria, which have become a popular research area recently as they not only can be more socially efficient than Nash equilibria but also are limits of algorithmic no-regret multi-agent learning dynamics. We discuss the basic properties of competitive mediator games and prove that in the generic setting of anonymous congestion(routing) games with market-share maximizing mediators all competitive mediator equilibria are monopolies whenever one of the mediators is weakly preferred to other mediators by all users. We apply and interpret these results in the context of new markets of competing ARAD service providers. We also provide a comprehensive overview of these markets and discuss the future mechanism design thereof.
