更多胜利，更少合作：评估 Cicero 的外交博弈表现
More Victories, Less Cooperation: Assessing Cicero's Diplomacy Play
AI总结：
本文通过抽象语义表示标注和 24 局人机对战（超 200 小时）评估 Cicero 在《外交》中的沟通能力，发现其虽在战略上胜过人类，但因欺骗与说服能力不足，沟通协作仍有限。
摘要：
棋盘游戏《外交》（Diplomacy）是通信与协作人工智能的一个具有挑战性的场景。最著名的通信型《外交》AI Cicero 拥有卓越的战略能力，超过了人类玩家。然而，最优秀的《外交》玩家精通的是沟通，而不仅仅是战术，这正是该游戏作为 AI 挑战受到关注的原因。本工作旨在理解 Cicero 在沟通方面成功的程度。首先，我们用抽象语义表示（Abstract Meaning Representation）对游戏内通信进行标注，以将游戏内战术与一般语言区分开来。其次，我们让人类与 Cicero 进行了二十四局游戏，总计超过 200 个人类玩家小时的对抗。虽然 AI 能够持续胜过人类玩家，但 AI 与人类的沟通仍然有限，因为 AI 在欺骗和说服方面存在困难。这表明 Cicero 依赖策略，尚未实现通信与协作 AI 的全部承诺。
英文摘要：
The boardgame Diplomacy is a challenging setting for communicative and cooperative artificial intelligence. The most prominent communicative Diplomacy AI, Cicero, has excellent strategic abilities, exceeding human players. However, the best Diplomacy players master communication, not just tactics, which is why the game has received attention as an AI challenge. This work seeks to understand the degree to which Cicero succeeds at communication. First, we annotate in-game communication with abstract meaning representation to separate in-game tactics from general language. Second, we run two dozen games with humans and Cicero, totaling over 200 human-player hours of competition. While AI can consistently outplay human players, AI-Human communication is still limited because of AI's difficulty with deception and persuasion. This shows that Cicero relies on strategy and has not yet reached the full promise of communicative and cooperative AI.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
