Collaboration is an integral part of human dialogue. Typical task-oriented dialogue games assign asymmetric roles to the participants, which limits their ability to elicit naturalistic role-taking in collaboration and its negotiation. We present a novel and simple online setup that favors balanced collaboration: a two-player 2D object placement game in which the players must negotiate the goal state themselves. We show empirically that human players exhibit a variety of role distributions, and that balanced collaboration improves task performance. We also present an LLM-based baseline agent which demonstrates that automatic playing of our game is an interesting challenge for artificial systems.

翻译：协作是人类对话不可或缺的组成部分。典型的面向任务的对话游戏为参与者分配了不对称的角色，这限制了它们在引发自然主义的角色承担及其协商方面的能力。我们提出了一种新颖且简单的在线设置，该设置有利于平衡协作：一个双人2D物体放置游戏，玩家必须自行协商目标状态。我们通过实证表明，人类玩家展现出多样化的角色分布，并且平衡协作能提高任务表现。我们还提出了一种基于LLM的基线智能体，它证明了自动玩我们的游戏对人工智能系统而言是一个有趣的挑战。