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A weighted constraint satisfaction approach to human goal-directed decision making
When we plan for long-range goals, proximal information cannot be exploited in a blindly myopic way, as relevant future information must also be considered. But when a subgoal must be resolved first, irrelevant future information should not interfere with the processing of more proximal, subgoal-rel...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9255770/ https://www.ncbi.nlm.nih.gov/pubmed/35709299 http://dx.doi.org/10.1371/journal.pcbi.1009553 |
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author | Li, Yuxuan McClelland, James L. |
author_facet | Li, Yuxuan McClelland, James L. |
author_sort | Li, Yuxuan |
collection | PubMed |
description | When we plan for long-range goals, proximal information cannot be exploited in a blindly myopic way, as relevant future information must also be considered. But when a subgoal must be resolved first, irrelevant future information should not interfere with the processing of more proximal, subgoal-relevant information. We explore the idea that decision making in both situations relies on the flexible modulation of the degree to which different pieces of information under consideration are weighted, rather than explicitly decomposing a problem into smaller parts and solving each part independently. We asked participants to find the shortest goal-reaching paths in mazes and modeled their initial path choices as a noisy, weighted information integration process. In a base task where choosing the optimal initial path required weighting starting-point and goal-proximal factors equally, participants did take both constraints into account, with participants who made more accurate choices tending to exhibit more balanced weighting. The base task was then embedded as an initial subtask in a larger maze, where the same two factors constrained the optimal path to a subgoal, and the final goal position was irrelevant to the initial path choice. In this more complex task, participants’ choices reflected predominant consideration of the subgoal-relevant constraints, but also some influence of the initially-irrelevant final goal. More accurate participants placed much less weight on the optimality-irrelevant goal and again tended to weight the two initially-relevant constraints more equally. These findings suggest that humans may rely on a graded, task-sensitive weighting of multiple constraints to generate approximately optimal decision outcomes in both hierarchical and non-hierarchical goal-directed tasks. |
format | Online Article Text |
id | pubmed-9255770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-92557702022-07-06 A weighted constraint satisfaction approach to human goal-directed decision making Li, Yuxuan McClelland, James L. PLoS Comput Biol Research Article When we plan for long-range goals, proximal information cannot be exploited in a blindly myopic way, as relevant future information must also be considered. But when a subgoal must be resolved first, irrelevant future information should not interfere with the processing of more proximal, subgoal-relevant information. We explore the idea that decision making in both situations relies on the flexible modulation of the degree to which different pieces of information under consideration are weighted, rather than explicitly decomposing a problem into smaller parts and solving each part independently. We asked participants to find the shortest goal-reaching paths in mazes and modeled their initial path choices as a noisy, weighted information integration process. In a base task where choosing the optimal initial path required weighting starting-point and goal-proximal factors equally, participants did take both constraints into account, with participants who made more accurate choices tending to exhibit more balanced weighting. The base task was then embedded as an initial subtask in a larger maze, where the same two factors constrained the optimal path to a subgoal, and the final goal position was irrelevant to the initial path choice. In this more complex task, participants’ choices reflected predominant consideration of the subgoal-relevant constraints, but also some influence of the initially-irrelevant final goal. More accurate participants placed much less weight on the optimality-irrelevant goal and again tended to weight the two initially-relevant constraints more equally. These findings suggest that humans may rely on a graded, task-sensitive weighting of multiple constraints to generate approximately optimal decision outcomes in both hierarchical and non-hierarchical goal-directed tasks. Public Library of Science 2022-06-16 /pmc/articles/PMC9255770/ /pubmed/35709299 http://dx.doi.org/10.1371/journal.pcbi.1009553 Text en © 2022 Li, McClelland https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Li, Yuxuan McClelland, James L. A weighted constraint satisfaction approach to human goal-directed decision making |
title | A weighted constraint satisfaction approach to human goal-directed decision making |
title_full | A weighted constraint satisfaction approach to human goal-directed decision making |
title_fullStr | A weighted constraint satisfaction approach to human goal-directed decision making |
title_full_unstemmed | A weighted constraint satisfaction approach to human goal-directed decision making |
title_short | A weighted constraint satisfaction approach to human goal-directed decision making |
title_sort | weighted constraint satisfaction approach to human goal-directed decision making |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9255770/ https://www.ncbi.nlm.nih.gov/pubmed/35709299 http://dx.doi.org/10.1371/journal.pcbi.1009553 |
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