Review of Multi-Agent Algorithms for Collective Behavior: a Structural Taxonomy

In this paper, we review multi-agent collective behavior algorithms in the literature and classify them according to their underlying mathematical structure. For each mathematical technique, we identify the multi-agent coordination tasks it can be applied to, and we analyze its scalability, bandwidth use, and demonstrated maturity. We highlight how versatile techniques such as artificial potential functions can be used for applications ranging from low-level position control to high-level coordination and task allocation, we discuss possible reasons for the slow adoption of complex distributed coordination algorithms in the field, and we highlight areas for further research and development.

• Publication year

  2018

• Venue

  arXiv.org

• Publication date

  2018-03-14

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1016/J.IFACOL.2018.07.097arXiv 1803.05464
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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