  We study the problem of finding robust equilibria in multiplayer concurrent
games with mean payoff objectives. A $(k,t)$-robust equilibrium is a strategy
profile such that no coalition of size $k$ can improve the payoff of one its
member by deviating, and no coalition of size $t$ can decrease the payoff of
other players. We are interested in pure equilibria, that is, solutions that
can be implemented using non-randomized strategies. We suggest a general
transformation from multiplayer games to two-player games such that pure
equilibria in the first game correspond to winning strategies in the second
one. We then devise from this transformation, an algorithm which computes
equilibria in mean-payoff games. Robust equilibria in mean-payoff games reduce
to winning strategies in multidimensional mean-payoff games for some threshold
satisfying some constraints. We then show that the existence of such equilibria
can be decided in polynomial space, and that the decision problem is
PSPACE-complete.
