research-article

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Extending MAPE-K to support human-machine teaming

Authors:

Jane Cleland-Huang,

Michael Vierhauser,

Michael Murphy,

Mike PrietoAuthors Info & Claims

SEAMS '22: Proceedings of the 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems

Pages 120 - 131

https://doi.org/10.1145/3524844.3528054

Published: 15 August 2022 Publication History

Abstract

The MAPE-K feedback loop has been established as the primary reference model for self-adaptive and autonomous systems in domains such as autonomous driving, robotics, and Cyber-Physical Systems. At the same time, the Human Machine Teaming (HMT) paradigm is designed to promote partnerships between humans and autonomous machines. It goes far beyond the degree of collaboration expected in human-on-the-loop and human-in-the-loop systems and emphasizes interactions, partnership, and teamwork between humans and machines. However, while MAPE-K enables fully autonomous behavior, it does not explicitly address the interactions between humans and machines as intended by HMT. In this paper, we present the MAPE-K_HMT framework which augments the traditional MAPE-K loop with support for HMT. We identify critical human-machine teaming factors and describe the infrastructure needed across the various phases of the MAPE-K loop in order to effectively support HMT. This includes runtime models that are constructed and populated dynamically across monitoring, analysis, planning, and execution phases to support human-machine partnerships. We illustrate MAPE-K_HMT using examples from an autonomous multi-UAV emergency response system, and present guidelines for integrating HMT into MAPE-K.

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Index Terms

Extending MAPE-K to support human-machine teaming
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models
    2. Interaction paradigms
      1. Collaborative interaction

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cover image ACM Conferences

SEAMS '22: Proceedings of the 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems

May 2022

193 pages

ISBN:9781450393058

DOI:10.1145/3524844

General Chair:
Bradley Schmerl
Carnegie Mellon University
,
Program Chairs:
Martina Maggio
Saarland University, Germany
,
Javier Cámara
University of Málaga, Spain

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May 18 - 23, 2022

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Cited By

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https://dl.acm.org/doi/10.1145/3698768
Jalalvand FBaruwal Chhetri MNepal SParis C(2024)Alert Prioritisation in Security Operations Centres: A Systematic Survey on Criteria and MethodsACM Computing Surveys10.1145/3695462Online publication date: 14-Sep-2024
https://doi.org/10.1145/3695462
Bernal AScheirer WCleland-Huang J(2024)NOMAD: A Natural, Occluded, Multi-scale Aerial Dataset, for Emergency Response Scenarios2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)10.1109/WACV57701.2024.00839(8569-8580)Online publication date: 3-Jan-2024
https://doi.org/10.1109/WACV57701.2024.00839
Andreoni MLunardi WLawton GThakkar S(2024)Enhancing Autonomous System Security and Resilience With Generative AI: A Comprehensive SurveyIEEE Access10.1109/ACCESS.2024.343936312(109470-109493)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3439363
Purandare SSinha UIslam MCleland-Huang JCohen M(2023)Self-Adaptive Mechanisms for Misconfigurations in Small Uncrewed Aerial Systems2023 IEEE/ACM 18th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS)10.1109/SEAMS59076.2023.00030(169-180)Online publication date: May-2023
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