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A taxonomy for multi-agent robotics

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Abstract

A key difficulty in the design of multi-agent robotic systems is the size and complexity of the space of possible designs. In order to make principled design decisions, an understanding of the many possible system configurations is essential. To this end, we present a taxonomy that classifies multi-agent systems according to communication, computational and other capabilities. We survey existing efforts involving multi-agent systems according to their positions in the taxonomy. We also present additional results concerning multi-agent systems, with the dual purposes of illustrating the usefulness of the taxonomy in simplifying discourse about robot collective properties, and also demonstrating that a collective can be demonstrably more powerful than a single unit of the collective.

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Authors and Affiliations

  1. Centre for Intelligent Machines, McGill University, Montreal, Quebec, Canada

    Gregory Dudek

  2. Department of Computer Science, York University, North York, Ontario, Canada

    Michael R. M. Jenkin, Evangelos Milios & David Wilkes

Authors
  1. Gregory Dudek
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  2. Michael R. M. Jenkin
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  3. Evangelos Milios
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  4. David Wilkes
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The support of NSERC Canada is greatfully acknowledged.

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Dudek, G., Jenkin, M.R.M., Milios, E. et al. A taxonomy for multi-agent robotics. Auton Robot 3, 375–397 (1996). https://doi.org/10.1007/BF00240651

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