opts

1 files changed, 2 insertions, 2 deletions

diff --git a/problem.tex b/problem.tex
index 2a40185..98ca4ac 100644
--- a/problem.tex
+++ b/problem.tex
@@ -49,7 +49,7 @@ knowledge; the objective of the buyer in this context is to select a set $S$
 maximizing the value $V(S)$ subject to the constraint $\sum_{i\in S} c_i\leq
 B$. We write:
 \begin{equation}\label{eq:non-strategic}
-    OPT(V,\mathcal{N}, B) = \max_{S\subseteq\mathcal{N}} \left\{V(S) \mid
+    OPT = \max_{S\subseteq\mathcal{N}} \left\{V(S) \mid
     \sum_{i\in S}c_i\leq B\right\}
 \end{equation}
 for the optimal value achievable in the full-information case. %\stratis{Should be $OPT(V,c,B)$\ldots better drop the arguments here and introduce them wherever necessary.}
@@ -82,7 +82,7 @@ A mechanism is truthful iff  every $i \in \mathcal{N}$ and every two cost vector
     \eqref{eq:non-strategic}. Formally, there must exist some $\alpha\geq 1$
     such that:
     \begin{displaymath}
-        OPT(V,\mathcal{N}, B) \leq \alpha V(S).
+        OPT \leq \alpha V(S).
     \end{displaymath}
     The approximation ratio captures the \emph{price of truthfulness}, \emph{i.e.},  the relative value loss incurred by adding the truthfulness constraint. % to the value function maximization.
     \item \emph{Computational efficiency.} The allocation and payment function