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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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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. |
format | Online Article Text |
id | pubmed-7566173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
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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