Distributed Search and Decision-Making using Cooperative Coevolutionary Agents
Raj Subbu, Arthur C. Sanderson · 2002
This paper presents a class of cooperative coevolu-tionary algorithms executing in a distributed informa-tion architecture consisting of coevolutionary agents, mobile software agents, and databases for superior network-efficient search and consequent distributed decision-making. In this approach to distributed decision-making, an objective function guides the con-current search for logically interrelated information re-siding in databases widely distributed over a heteroge-neous network environment. The information in these databases is logically interrelated due to the objective function that guides the decision-making. Applica-tion examples from the fields of manufacturing plan-ning, intelligent internet search, and internet traffic management are utilized to highlight the applicability of this basic approach to network-efficient distributed decision-making.