Abstract
Constraint Games are a recent framework proposed
to model and solve static games where Constraint
Programming is used to express players preferences. In this paper, we rethink their solving technique in terms of constraint propagation by considering players preferences as global constraints. It
yields not only a more elegant but also a more effi-
cient framework. Our new complete solver is faster
than previous state-of-the-art and is able to find
all pure Nash equilibria for some problems with
200 players. We also show that performances can
greatly be improved for graphical games, allowing
some games with 2000 players to be solved.