  Dynamics in a distributed system are self-stabilizing if they are guaranteed
to reach a stable state regardless of how the system is initialized. Game
dynamics are uncoupled if each player's behavior is independent of the other
players' preferences. Recognizing an equilibrium in this setting is a
distributed computational task. Self-stabilizing uncoupled dynamics, then, have
both resilience to arbitrary initial states and distribution of knowledge. We
study these dynamics by analyzing their behavior in a bounded-recall
synchronous environment. We determine, for every "size" of game, the minimum
number of periods of play that stochastic (randomized) players must recall in
order for uncoupled dynamics to be self-stabilizing. We also do this for the
special case when the game is guaranteed to have unique best replies. For
deterministic players, we demonstrate two self-stabilizing uncoupled protocols.
One applies to all games and uses three steps of recall. The other uses two
steps of recall and applies to games where each player has at least four
available actions. For uncoupled deterministic players, we prove that a single
step of recall is insufficient to achieve self-stabilization, regardless of the
number of available actions.
