Asymmetry in learning automata playing multi-level games

To achieve synergy, it is important for agents to form cooperative groups such that shared resources, strategies, and information can be fully utilized. A game-theoretic model is presented in which agents decide whether it is beneficial to form groups and what actions to take within the chosen context. Learning automata are used to model this multi-level decisionmaking process. The results show that asymmetries in initialization and equilibria do not effect this process. With delayed information, both symmetric and asymmetric penalities lead to chaos but with different Lyapunov exponents.