  The notion of optimality naturally arises in many areas of applied
mathematics and computer science concerned with decision making. Here we
consider this notion in the context of two formalisms used for different
purposes and in different research areas: graphical games and soft constraints.
We relate the notion of optimality used in the area of soft constraint
satisfaction problems (SCSPs) to that used in graphical games, showing that for
a large class of SCSPs that includes weighted constraints every optimal
solution corresponds to a Nash equilibrium that is also a Pareto efficient
joint strategy.
