  This paper addresses a coordination problem between two agents (Agents $1$
and $2$) in the presence of a noisy communication channel which depends on an
external system state $\{x_{0,t}\}$. The channel takes as inputs both agents'
actions, $\{x_{1,t}\}$ and $\{x_{2,t}\}$ and produces outputs that are observed
strictly causally at Agent $2$ but not at Agent $1$. The system state is
available either causally or non-causally at Agent $1$ but unknown at Agent
$2$. Necessary and sufficient conditions on a joint distribution
$\bar{Q}(x_0,x_1,x_2)$ to be implementable asymptotically (i.e, when the number
of taken actions grows large) are provided for both causal and non-causal state
information at Agent $1$.
  Since the coordination degree between the agents' actions, $x_{1,t}$ and
$x_{2,t}$, and the system state $x_{0,t}$ is measured in terms of an average
payoff function, feasible payoffs are fully characterized by implementable
joint distributions. In this sense, our results allow us to derive the
performance of optimal power control policies on an interference channel and to
assess the gain provided by non-causal knowledge of the system state at Agent
$1$.
  The derived proofs readily yield new results also for the problem of
state-amplification under a causality constraint at the decoder.
