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Aligning Teams to the Future: Adapting Human-Machine Teams via Free Energy

  • Adam FouseEmail author
  • Georgiy Levchuk
  • Nathan Schurr
  • Robert McCormack
  • Krishna Pattipati
  • Daniel Serfaty
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 903)

Abstract

Future hybrid human-machine teams will need to optimize their performance in uncertain environments by adapting their team structure. To address this need, we have developed a framework based on minimization of variational free energy, an information theoretic measure that has been shown to account for a variety of biological self-organizing phenomena. This paper proposes a novel approach to balance team structure by adapting roles and relationships based upon this framework. We apply this approach to evaluate possible structures for an infantry squad of human soldiers and autonomous systems. Using our STATES team simulation environment, we simulate mission performance for these teams and demonstrate that this approach enables a 12-person team to achieve performance results on par with a 15-person traditional team in terms of mission execution time. We argue that these results indicate that the free energy approach will lead to better hybrid team adaptations and improved performance.

Keywords

Human-machine teaming Team structure adaptation Adaptive teams Free energy Active inference 

Notes

Acknowledgements

This work was supported by the Defense Advanced Research Projects Agency through contract N66001-17-C-4053. We would like to thank Dr. John Paschkewitz for his guidance of this work. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the sponsors.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Adam Fouse
    • 1
    Email author
  • Georgiy Levchuk
    • 1
  • Nathan Schurr
    • 1
  • Robert McCormack
    • 1
  • Krishna Pattipati
    • 2
  • Daniel Serfaty
    • 1
  1. 1.Aptima, Inc.WoburnUSA
  2. 2.University of ConnecticutStorrsUSA

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