We model this behavior with distributed game automata which are adaptive decision-makers with aged information concerning the strategies of each other. We focus on the performance of these decision-makers with respect to the amount of communication. That is, agents may decide to work alone or to work together in groups to derive a mutual benefit. Simulation of a static load balancing application shows that, with sufficient communication, an adaptive strategy in dynamic group formation is globally optimal.
Analysis indicates the potential for poor decisions when the agents communicate infrequently.
The results illustrate the fundamental nature of the uncertainty present in any distributed system.