Improving the scalability of multi-agent systems

Abstract

There is an increasing demand for designers and developers to construct ever larger multi-agent systems. Such systems will be com- posed of hundreds or even thousands of autonomous agents. Moreover, in open and dynamic environments, the number of agents in the sys- tem at any one time will uctuate significantly. To cope with these twin issues of scalability and variable numbers, we hypothesize that multi- agent systems need to be both self-building (able to determine the most appropriate organizational structure for the system by themselves at run- time) and adaptive (able to change this structure as their environment changes). To evaluate this hypothesis we have implemented such amulti- agent system and have applied it to the domain of automated trading. Preliminary results supporting the first part of this hypothesis are pre- sented: adaption and self-organization do indeed make the system better able to cope with large numbers of agents.