Abstract
Organization is an important mechanism for improving performance in complex multiagent systems. Yet, little consideration has been given to the performance gain that organization can provide across a broad range of conditions. Intuitively, when agents are mostly idle, organization offers little benefit. In such settings, almost any organization—appropriate, inappropriate, or absent—leads to agents accomplishing the needed work. Conversely, when every agent is severely overloaded, no choice of agent activities achieves system objectives. Only as the overall workload approaches the limit of agents’ capabilities is effective organization crucial to success.
We explored this organizational “sweet spot” intuition by examining the effectiveness of two previously published implementations of organized software agents when they are operated under a wide range of conditions: (1) call-center agents extinguishing RoboCup Rescue fires and (2) agents learning network task-distribution policies that optimize service time. In both cases, organizational effect diminished significantly outside the sweet spot. Detailed measures taken of coordination and cooperation amounts, lost work opportunities, and exceeded span-of-control limits account for this behavior. Such measures can be used to assess the potential benefit of organization in a specific setting and whether the organization design must be a highly effective one.
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Notes
- 1.
Belief-desire-intention model of agency [12].
- 2.
For example, a typical phase-transition performance plot, such as Fig. 4 in the classic Kirkpatrick and Selman SAT phase-change paper [18] shows the performance cliff that occurs at the phase boundary, which shifts laterally under different conditions. If such a figure is redrawn as relative difference curves from a baseline condition (such as the k = 6/N = 40 values in that figure), it reveals wide “sweet spot” curves similar to the curves shown in this paper. Relative plots highlight the span and magnitude of performance differences near the phase change, and we consider them more informative in highlighting sweet-spot regions than raw performance-value plots.
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Acknowledgment
This material is based in part upon work supported by the National Science Foundation under Awards No. IIS-0964590 and IIS-1116078. Any opinions, findings, conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Corkill, D.D., Garant, D., Lesser, V.R. (2016). Exploring the Effectiveness of Agent Organizations. In: Dignum, V., Noriega, P., Sensoy, M., Sichman, J. (eds) Coordination, Organizations, Institutions, and Norms in Agent Systems XI. COIN 2015. Lecture Notes in Computer Science(), vol 9628. Springer, Cham. https://doi.org/10.1007/978-3-319-42691-4_5
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