Information processing for a finite resource allocation mechanism

We deal with an 'organization' having m individual agents (the 'agents') and one central agent or agency (the 'coordinator'), and the problem of allocating a fixed supply of n commodities among the agents. The coordinator wishes to distribute the commodities in such a way as to maximize an objective function whose arguments are functions known (implicitly) to the individual agents, but not to the coordinator. The more information the coordinator obtains about the individual agents' functions, the better the allocation decision he or she can make; however, gaining such information is costly, so that the coordinator must balance the potential gain against the cost of acquiring additional information. We find a 'satisficing' solution to this problem which is computable and which terminates in a finite number of steps.