Towards a Dynamic Selection and Configuration of Adaptation Strategies in Augmented Cognition

Fuchs, Sven; Schwarz, Jessica

doi:10.1007/978-3-319-58625-0_7

Cited by 18 publications

(6 citation statements)

References 12 publications

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“…Thus, in real user cases multiple sources of data need to be integrated and interpreted so that the system response works in real time and is context-sensitive (Fuchs and Schwarz, 2017;Fuchs et al, 2007;Patel et al, 2017). To make the loop between the user and the computer seamless, 10iocybernetics adaptation (e.g., Stephens et al, 2018) and similar methods can be considered.…”

Section: Augmented Cognitionmentioning

confidence: 99%

Human augmentation: Past, present and future

Raisamo

Rakkolainen

Majaranta

et al. 2019

International Journal of Human-Computer Studies

156

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Human augmentation is a field of research that aims to enhance human abilities through medicine or technology. This has historically been achieved by consuming chemical substances that improve a selected ability or by installing implants which require medical operations. Both of these methods of augmentation can be invasive. Augmented abilities have also been achieved with external tools, such as eyeglasses, binoculars, microscopes or highly sensitive microphones. Lately, augmented reality and multimodal interaction technologies have enabled non-invasive ways to augment human.In this article, we first discuss the field and related terms. We provide relevant definitions based on the present understanding of the field. This is followed by a summary of existing work in augmented senses, action, and cognition. Our contribution to the future includes a model for wearable augmentation. In addition, we present a call for research to realize this vision. Then, we discuss future human abilities. Wearable technologies may act as mediators for human augmentation, in the same manner as eyeglasses once revolutionized human vision. Non-invasive and easy-to-use wearable extensions will enable lengthening the active life for aging citizens or supporting the full inclusion of people with special needs in society, but there are also potential problems. Therefore, we conclude by discussing ethical and societal issues: privacy, social manipulation, autonomy and side effects, accessibility, safety and balance, and unpredictable future.

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Section: Augmented Cognitionmentioning

confidence: 99%

Human augmentation: Past, present and future

Raisamo

Rakkolainen

Majaranta

et al. 2019

International Journal of Human-Computer Studies

156

View full text Add to dashboard Cite

show abstract

“…These systems resume the default setting once the trigger is no longer active. However, as the situation and context evolve, the once-adequate adaptation strategy applied by conventional adaptive systems may become inadequate ( Fuchs and Schwarz, 2017 ). To address this problem, dynamic adaptations based on a diverse set of indicators are required.…”

Section: Framework For Adaptive Autonomy In Human-swarm Interactionmentioning

confidence: 99%

Characterization of Indicators for Adaptive Human-Swarm Teaming

et al. 2022

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Swarm systems consist of large numbers of agents that collaborate autonomously. With an appropriate level of human control, swarm systems could be applied in a variety of contexts ranging from urban search and rescue situations to cyber defence. However, the successful deployment of the swarm in such applications is conditioned by the effective coupling between human and swarm. While adaptive autonomy promises to provide enhanced performance in human-machine interaction, distinct factors must be considered for its implementation within human-swarm interaction. This paper reviews the multidisciplinary literature on different aspects contributing to the facilitation of adaptive autonomy in human-swarm interaction. Specifically, five aspects that are necessary for an adaptive agent to operate properly are considered and discussed, including mission objectives, interaction, mission complexity, automation levels, and human states. We distill the corresponding indicators in each of the five aspects, and propose a framework, named MICAH (i.e., Mission-Interaction-Complexity-Automation-Human), which maps the primitive state indicators needed for adaptive human-swarm teaming.

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“…Most adaptive systems have focused on a single human state construct to determine adaptations, but a multi-dimensional adaptation scheme has been theorized [4], [12]. The "Real-Time Assessment of Multidimensional User State" system was intended to assess cognitive workload, fatigue, and attentional focus in order to adapt a system's interactions intelligently, but only recognized high workload or high fatigue.…”

Section: Related Workmentioning

confidence: 99%

SAHRTA: A Supervisory-Based Adaptive Human-Robot Teaming Architecture

Heard¹,

Fortune²,

Adams³

2020

Preprint

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Supervisory-based human-robot teams are deployed in various dynamic and extreme environments (e.g., space exploration). Achieving high task performance in such environments is critical, as a mistake may lead to significant monetary loss or human injury. Task performance may be augmented by adapting the supervisory interface's interactions or autonomy levels based on the human supervisor's workload level, as workload is related to task performance. Typical adaptive systems rely solely on the human's overall or cognitive workload state to select what adaptation strategy to implement; however, overall workload encompasses many dimensions (i.e., cognitive, physical, visual, auditory, and speech) called workload components. Selecting an appropriate adaptation strategy based on a complete human workload state (rather than a single workload dimension) may allow for more impactful adaptations that ensure high task performance. A Supervisory-Based Adaptive Human-Robot Teaming Architecture (SAHRTA) that selects an appropriate level of autonomy or system interaction based on a complete realtime multi-dimensional workload estimate and predicted future task performance is introduced. SAHRTA was shown to improve overall task performance in a physically expanded version of the NASA Multi-Attribute Task Battery.

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Towards a Dynamic Selection and Configuration of Adaptation Strategies in Augmented Cognition

Cited by 18 publications

References 12 publications

Human augmentation: Past, present and future

Human augmentation: Past, present and future

Characterization of Indicators for Adaptive Human-Swarm Teaming

SAHRTA: A Supervisory-Based Adaptive Human-Robot Teaming Architecture

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