The Impact of Vertical Specialization on Hierarchical Multi-Agent Systems

Steven Okamoto, Paul Scerri, Katia Sycara

Hierarchies are one of the most common organizational structures observed in multi-agent systems. In this paper we study vertical specialization as a reason for hierarchical structures. In vertically specialized systems, more highly skilled agents are also more costly. By using less capable agents to initially process tasks and forwarding only exceptional tasks to more capable agents, such systems may be able to economize on the number of highly capable agents. The result is a hierarchical structure with least capable agents at the bottom. However, such a structure increases the delay in completing some tasks, because they must pass through multiple levels of control. Thus, vertical specialization presents a tradeoff between economizing on skilled agents and increasing task completion time. We find that for a wide range of settings, vertical specialization induces an optimal hierarchy of height at most three. This suggests that a multi-agent system designer interested in exploiting vertical specialization needs to use at most three levels of specialization in order to reap most of the benefits.

Subjects: 7.1 Multi-Agent Systems; 7. Distributed AI

Submitted: Apr 15, 2008

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