  In a two-player game, two cooperating but non communicating players, Alice
and Bob, receive inputs taken from a probability distribution. Each of them
produces an output and they win the game if they satisfy some predicate on
their inputs/outputs. The entangled value $\omega^*(G)$ of a game $G$ is the
maximum probability that Alice and Bob can win the game if they are allowed to
share an entangled state prior to receiving their inputs.
  The $n$-fold parallel repetition $G^n$ of $G$ consists of $n$ instances of
$G$ where the players receive all the inputs at the same time and produce all
the outputs at the same time. They win $G^n$ if they win each instance of $G$.
  In this paper we show that for any game $G$ such that $\omega^*(G) = 1 -
\varepsilon < 1$, $\omega^*(G^n)$ decreases exponentially in $n$. First, for
any game $G$ on the uniform distribution, we show that $\omega^*(G^n) = (1 -
\varepsilon^2)^{\Omega\left(\frac{n}{\log(|I||O|)} -
|\log(\varepsilon)|\right)}$, where $|I|$ and $|O|$ are the sizes of the input
and output sets. From this result, we show that for any entangled game $G$,
$\omega^*(G^n) \le (1 - \varepsilon^2)^{\Omega(\frac{n}{Q\log(|I||O|)} -
\frac{|\log(\varepsilon)|}{Q})}$ where $p$ is the input distribution of $G$ and
$Q= \frac{|I|^2 \max_{xy} p_{xy}^2 }{\min_{xy} p_{xy} }$. This implies parallel
repetition with exponential decay as long as $\min_{xy} \{p_{xy}\} \neq 0$ for
general games. To prove this parallel repetition, we introduce the concept of
\emph{Superposed Information Cost} for entangled games which is inspired from
the information cost used in communication complexity.
