Evaluating Multi-Agent System Architectures

Paul Davidsson, BTH

Abstract

Much effort has been spent on suggesting and implementing new
architectures of Multi-Agent Systems. However, we believe the time has
come to compare and evaluate these architectures in a more systematic
way. Rather than just studying a particular application, we suggest
that more general problem domains corresponding to sets of
applications should be studied.  Similarly, we argue that it is more
useful to study the properties of classes of multi-agent system
architectures than particular architectures.  Also, it is important to
evaluate the architectures in several dimensions, both different
performance-related attributes, which are domain dependent and more
general quality attributes, such as, robustness, modifiability, and
scalability. As a case study we investigate the general problem of
"dynamic resource allocation" and present four classes of multi-agent
system architectures that solve this problem. These classes are
discriminated by their degree of distribution of control and degree of
synchronization. Finally, we instantiate each of these architecture
classes and evaluate, through simulation experiments, how they solve a
concrete dynamic resource allocation problem, namely load balancing
and overload control of Intelligent Networks.