Adaptive coordination in distributed systems with delayed communication

Abstract

A new model for distributed decision making, distributed game automata, focuses on how communication affects the quality of decisions. The goal is to limit communication between decision makers such that overhead costs are reduced but good decisions still result. Learning automata play repeated games with payoffs quantifying the performance in a distributed application. Each automaton's view of the global state is periodically updated by communication from other automata of their local state (i.e. current strategy probabilities). Because of infrequent communication and transmission delays, received state information may become stale: an example game illustrates the mutually conflicting decisions that can result. Simulation and analytic results show there exists a maximum communication delay before decision quality begins to suffer, however, with sufficient communication, the agents adapt to a coordinated policy. >