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Transparent Shepherding: A Rule-Based Learning Shepherd for Human Swarm Teaming

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Shepherding UxVs for Human-Swarm Teaming

Part of the book series: Unmanned System Technologies ((UST))

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Abstract

This chapter aims to demonstrate how rule-based Artificial Intelligence algorithms can address a few human swarm teaming challenges. We will start from the challenges identified by the cognitive engineering community for building human autonomy teaming and how they scale to human swarm teaming. The discussion will follow with a description of rule-based machine learning with a focus on learning classifier systems as a representative for these algorithms and their benefits for human swarm teaming. Shepherding affords a human to manage a swarm by teaming with an autonomous single shepherd. A learning classifier system is designed to learn behaviour needed to be exhibited by the shepherd. Results demonstrate the effectiveness of the rule-based XCS model to capture shepherding behaviour, where the XCS model achieves comparable performance to the standard Strömbom’s shepherding method as measured by the number of steps needed by a sheep-dog to guide group of sheep to target destination. These results are promising and demonstrate that learning classifier systems could design autonomous shepherds for new type of shepherding tasks and scenarios that we may not have rules for today.

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Authors and Affiliations

  1. School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia

    Essam Debie, Michael Barlow, Kathryn Kasmarik, Sreenatha Anavatti, Matthew Garratt & Hussein A. Abbass

  2. Faculty of Science and Technology, University of Canberra, Canberra, ACT, Australia

    Raul Fernandes Rojas

  3. Defence Science and Technology Group, Edinburgh, SA, Australia

    Justin Fidock

Authors
  1. Essam Debie
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  2. Raul Fernandes Rojas
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  3. Justin Fidock
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  4. Michael Barlow
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  5. Kathryn Kasmarik
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  6. Sreenatha Anavatti
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  7. Matthew Garratt
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  8. Hussein A. Abbass
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Correspondence to Essam Debie .

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Editors and Affiliations

  1. University of New South Wales, Canberra, ACT, Australia

    Hussein A. Abbass

  2. University of New South Wales, Canberra, ACT, Australia

    Robert A. Hunjet

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Debie, E. et al. (2021). Transparent Shepherding: A Rule-Based Learning Shepherd for Human Swarm Teaming. In: Abbass, H.A., Hunjet, R.A. (eds) Shepherding UxVs for Human-Swarm Teaming. Unmanned System Technologies. Springer, Cham. https://doi.org/10.1007/978-3-030-60898-9_12

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  • DOI: https://doi.org/10.1007/978-3-030-60898-9_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60897-2

  • Online ISBN: 978-3-030-60898-9

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