AI 中文总结
本文研究信息架构（如仪表盘、排行榜）如何通过透明度参数影响智能体的策略行为，提出认知层级模型，证明不透明性可充当复杂度乘数，并揭示其带来的复杂度税效应，为设计者提供可见性杠杆。
AI 中文摘要
仪表盘、信息流和排行榜决定了智能体认为自己在与谁博弈。我们研究此类信息架构如何塑造策略行为，以及控制这些架构的设计者如何将可见性用作一种杠杆。我们提出一个行为模型，其中透明度参数控制智能体如何有选择性地接触推理深度相近的对手，并将其嵌入认知层级环境中，该环境提供了一种易于处理的语言，将智能体对他人复杂程度的信念与其所见内容联系起来。我们证明，由于暴露算子是对类型分布的指数倾斜，透明度对总体行为的影响具有闭式解：总体行动对$p$的导数与感知复杂度的总体平均方差成正比。这一恒等式在策略互补博弈中确定了效应的方向（不透明性提高总体努力水平），在协调环境中（不透明性降低平均行动），并且对于任何对信念单调的响应规则，序数版本均成立。值得注意的是，在泊松先验下，不透明性充当复杂度乘数：每个推理者都表现得如同总体服从$\mathrm{Poisson}(\tau/p)$分布。我们利用这一结构来刻画面向协调的设计者所面临的异议与层级之间的权衡，识别对可见性响应最强烈的推理深度，并证明不透明性强加了一种“复杂度税”，在这种税下，最深层的推理者可能输给中等推理者。在智能体仅看到已发布行动的嘈杂排行榜的模拟中，同时复现了反转和税收效应。总之，我们的发现强调，智能体看到谁，而不仅仅是如何深入推理，塑造了策略行为，并将可见性指向为一种设计杠杆。
英文摘要
Dashboards, feeds, and leaderboards determine whom agents believe they are playing against. We study how such information architectures shape strategic behavior, and how a designer who controls them can use visibility as a lever. We propose a behavioral model in which a transparency parameter governs how selectively agents are exposed to opponents of nearby reasoning depth, and embed it in a Cognitive Hierarchy environment, which provides a tractable language for tying agents' beliefs about the sophistication of others to what they see. We show that because the exposure operator is an exponential tilt of the type distribution, the effect of transparency on aggregate behavior has a closed form: the derivative of the aggregate action with respect to $p$ is proportional to the population-average variance of perceived sophistication. This identity signs the effect in games of strategic complements (opacity raises aggregate effort) and in coordination environments (opacity lowers the mean action), and an ordinal version holds for any response rule that is monotone in the belief. Notably, under a Poisson prior, opacity acts as a sophistication multiplier: every reasoner plays as if the population were $\mathrm{Poisson}(τ/p)$. We use this structure to characterize the disagreement-versus-level tradeoff faced by a coordination-minded designer, to identify the reasoning depths that respond most to visibility, and to show that opacity imposes a ``sophistication tax'' under which the deepest reasoners can lose to moderate ones. Simulations in which agents see only a noisy leaderboard of published actions reproduce both the reversal and the tax. Together, our findings highlight that who an agent sees, and not only how deeply it reasons, shapes strategic behavior, and point to visibility as a design lever.
