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Cognitive Modeling of Automation Adaptation in a Time Critical Task

This paper presents a cognitive model that simulates an adaptation process to automation in a time-critical task. The paper uses a simple tracking task (which represents vehicle operation) to reveal how the reliance on automation changes as the success probabilities of the automatic and manual mode...

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Autores principales: Morita, Junya, Miwa, Kazuhisa, Maehigashi, Akihiro, Terai, Hitoshi, Kojima, Kazuaki, Ritter, Frank E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7566173/
https://www.ncbi.nlm.nih.gov/pubmed/33123033
http://dx.doi.org/10.3389/fpsyg.2020.02149
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author Morita, Junya
Miwa, Kazuhisa
Maehigashi, Akihiro
Terai, Hitoshi
Kojima, Kazuaki
Ritter, Frank E.
author_facet Morita, Junya
Miwa, Kazuhisa
Maehigashi, Akihiro
Terai, Hitoshi
Kojima, Kazuaki
Ritter, Frank E.
author_sort Morita, Junya
collection PubMed
description This paper presents a cognitive model that simulates an adaptation process to automation in a time-critical task. The paper uses a simple tracking task (which represents vehicle operation) to reveal how the reliance on automation changes as the success probabilities of the automatic and manual mode vary. The model was developed by using a cognitive architecture, ACT-R (Adaptive Control of Thought-Rational). We also introduce two methods of reinforcement learning: the summation of rewards over time and a gating mechanism. The model performs this task through productions that manage perception and motor control. The utility values of these productions are updated based on rewards in every perception-action cycle. A run of this model simulated the overall trends of the behavioral data such as the performance (tracking accuracy), the auto use ratio, and the number of switches between the two modes, suggesting some validity of the assumptions made in our model. This work shows how combining different paradigms of cognitive modeling can lead to practical representations and solutions to automation and trust in automation.
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spelling pubmed-75661732020-10-28 Cognitive Modeling of Automation Adaptation in a Time Critical Task Morita, Junya Miwa, Kazuhisa Maehigashi, Akihiro Terai, Hitoshi Kojima, Kazuaki Ritter, Frank E. Front Psychol Psychology This paper presents a cognitive model that simulates an adaptation process to automation in a time-critical task. The paper uses a simple tracking task (which represents vehicle operation) to reveal how the reliance on automation changes as the success probabilities of the automatic and manual mode vary. The model was developed by using a cognitive architecture, ACT-R (Adaptive Control of Thought-Rational). We also introduce two methods of reinforcement learning: the summation of rewards over time and a gating mechanism. The model performs this task through productions that manage perception and motor control. The utility values of these productions are updated based on rewards in every perception-action cycle. A run of this model simulated the overall trends of the behavioral data such as the performance (tracking accuracy), the auto use ratio, and the number of switches between the two modes, suggesting some validity of the assumptions made in our model. This work shows how combining different paradigms of cognitive modeling can lead to practical representations and solutions to automation and trust in automation. Frontiers Media S.A. 2020-10-02 /pmc/articles/PMC7566173/ /pubmed/33123033 http://dx.doi.org/10.3389/fpsyg.2020.02149 Text en Copyright © 2020 Morita, Miwa, Maehigashi, Terai, Kojima and Ritter. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Morita, Junya
Miwa, Kazuhisa
Maehigashi, Akihiro
Terai, Hitoshi
Kojima, Kazuaki
Ritter, Frank E.
Cognitive Modeling of Automation Adaptation in a Time Critical Task
title Cognitive Modeling of Automation Adaptation in a Time Critical Task
title_full Cognitive Modeling of Automation Adaptation in a Time Critical Task
title_fullStr Cognitive Modeling of Automation Adaptation in a Time Critical Task
title_full_unstemmed Cognitive Modeling of Automation Adaptation in a Time Critical Task
title_short Cognitive Modeling of Automation Adaptation in a Time Critical Task
title_sort cognitive modeling of automation adaptation in a time critical task
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7566173/
https://www.ncbi.nlm.nih.gov/pubmed/33123033
http://dx.doi.org/10.3389/fpsyg.2020.02149
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