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chore: updatimg emthodoloyg

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Daniel Rosel
2026-04-09 16:55:46 +02:00
parent e694d38bce
commit c0c375548c
3 changed files with 36 additions and 27 deletions
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paper/src/mirrors/cais2026/main.tex
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@@ -300,9 +300,9 @@ where $W_p$ is the $p$-Wasserstein distance and $\epsilon > 0$ is the ambiguity
The platform seeks a policy $\pi^*$ that maximizes worst-case revenue over the ambiguity set while penalizing information leakage to suspected agents:
\begin{equation}
\label{eq:robust_policy}
\pi^* = \arg \max_{\pi} \min_{Q \in \mathcal{U}_\epsilon} \; \mathbb{E}_{d \sim Q} \left[ R(p, d) - \lambda \cdot \text{COI}_{\text{leak}}(p, \tau') - \eta \cdot \text{UX}(\tau', p) \right]
\pi^* = \arg \max_{\pi} \min_{Q \in \mathcal{U}_\epsilon} \; \mathbb{E}_{d \sim Q} \left[ R(p, d) - \lambda \cdot \text{COI}_{\text{leak}}(p, \tau') - \eta_{\text{ux}} \cdot \text{UX}(\tau', p) \right]
\end{equation}
where $R(p, d) = p \cdot d$ is the revenue function.
where $R(p, d) = p \cdot d$ is the revenue function, $\lambda$ scales COI leakage, and $\eta_{\text{ux}}$ scales the UX penalty with $\text{UX}(\tau', p)\in[0,1]$.
\begin{definition}[COI Leakage]
The per-query information leakage cost is: