Cargando…

Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence

Exposure to a chemical is a critical consideration in the assessment of risk, as it adds real-world context to toxicological information. Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments...

Descripción completa

Detalles Bibliográficos
Autores principales: Brandon, Namdi, Dionisio, Kathie L., Isaacs, Kristin, Tornero-Velez, Rogelio, Kapraun, Dustin, Setzer, R. Woodrow, Price, Paul S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6914672/
https://www.ncbi.nlm.nih.gov/pubmed/30242268
http://dx.doi.org/10.1038/s41370-018-0052-y
_version_ 1783479855339274240
author Brandon, Namdi
Dionisio, Kathie L.
Isaacs, Kristin
Tornero-Velez, Rogelio
Kapraun, Dustin
Setzer, R. Woodrow
Price, Paul S.
author_facet Brandon, Namdi
Dionisio, Kathie L.
Isaacs, Kristin
Tornero-Velez, Rogelio
Kapraun, Dustin
Setzer, R. Woodrow
Price, Paul S.
author_sort Brandon, Namdi
collection PubMed
description Exposure to a chemical is a critical consideration in the assessment of risk, as it adds real-world context to toxicological information. Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that simulates longitudinal patterns in human behavior. By basing the ABM upon an artificial intelligence (AI) system, we create agents that mimic human decisions on performing behaviors relevant for determining exposures to chemicals and other stressors. We implement the ABM in a computer program called the Agent-Based Model of Human Activity Patterns (ABMHAP) that predicts the longitudinal patterns for sleeping, eating, commuting, and working. We then show that ABMHAP is capable of simulating behavior over extended periods of time. We propose that this framework, and models based on it, can generate longitudinal human behavior data for use in exposure assessments.
format Online
Article
Text
id pubmed-6914672
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher Nature Publishing Group US
record_format MEDLINE/PubMed
spelling pubmed-69146722019-12-20 Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence Brandon, Namdi Dionisio, Kathie L. Isaacs, Kristin Tornero-Velez, Rogelio Kapraun, Dustin Setzer, R. Woodrow Price, Paul S. J Expo Sci Environ Epidemiol Article Exposure to a chemical is a critical consideration in the assessment of risk, as it adds real-world context to toxicological information. Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that simulates longitudinal patterns in human behavior. By basing the ABM upon an artificial intelligence (AI) system, we create agents that mimic human decisions on performing behaviors relevant for determining exposures to chemicals and other stressors. We implement the ABM in a computer program called the Agent-Based Model of Human Activity Patterns (ABMHAP) that predicts the longitudinal patterns for sleeping, eating, commuting, and working. We then show that ABMHAP is capable of simulating behavior over extended periods of time. We propose that this framework, and models based on it, can generate longitudinal human behavior data for use in exposure assessments. Nature Publishing Group US 2018-09-21 2020 /pmc/articles/PMC6914672/ /pubmed/30242268 http://dx.doi.org/10.1038/s41370-018-0052-y Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Brandon, Namdi
Dionisio, Kathie L.
Isaacs, Kristin
Tornero-Velez, Rogelio
Kapraun, Dustin
Setzer, R. Woodrow
Price, Paul S.
Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence
title Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence
title_full Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence
title_fullStr Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence
title_full_unstemmed Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence
title_short Simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence
title_sort simulating exposure-related behaviors using agent-based models embedded with needs-based artificial intelligence
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6914672/
https://www.ncbi.nlm.nih.gov/pubmed/30242268
http://dx.doi.org/10.1038/s41370-018-0052-y
work_keys_str_mv AT brandonnamdi simulatingexposurerelatedbehaviorsusingagentbasedmodelsembeddedwithneedsbasedartificialintelligence
AT dionisiokathiel simulatingexposurerelatedbehaviorsusingagentbasedmodelsembeddedwithneedsbasedartificialintelligence
AT isaacskristin simulatingexposurerelatedbehaviorsusingagentbasedmodelsembeddedwithneedsbasedartificialintelligence
AT tornerovelezrogelio simulatingexposurerelatedbehaviorsusingagentbasedmodelsembeddedwithneedsbasedartificialintelligence
AT kapraundustin simulatingexposurerelatedbehaviorsusingagentbasedmodelsembeddedwithneedsbasedartificialintelligence
AT setzerrwoodrow simulatingexposurerelatedbehaviorsusingagentbasedmodelsembeddedwithneedsbasedartificialintelligence
AT pricepauls simulatingexposurerelatedbehaviorsusingagentbasedmodelsembeddedwithneedsbasedartificialintelligence