  Distributed decision-makers are modeled as players in a game with two levels.
High level decisions concern the game environment and determine the willingness
of the players to form a coalition (or group). Low level decisions involve the
actions to be implemented within the chosen environment. Coalition and action
strategies are determined by probability distributions, which are updated using
learning automata schemes. The payoffs are also probabilistic and there is
uncertainty in the state vector since information is delayed. The goal is to
reach equilibrium in both levels of decision making; the results show the
conditions for instability, based on the age of information.
