We consider a signaling game originally introduced by Skyrms, which models
how two interacting players learn to signal each other and thus create a common
language. The first rigorous analysis was done by Argiento, Pemantle, Skyrms
and Volkov (2009) with 2 states, 2 signals and 2 acts. We study the case of M_1
states, M_2 signals and M_1 acts for general M_1, M_2. We prove that the
expected payoff increases in average and thus converges a.s., and that a limit
bipartite graph emerges, such that no signal-state correspondence is associated
to both a synonym and an informational bottleneck. Finally, we show that any
graph correspondence with the above property is a limit configuration with
positive probability.