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Adaptive planning depth in human problem-solving.

作者信息

Eluchans Mattia, Lancia Gian Luca, Maselli Antonella, D'Alessandro Marco, Gordon Jeremy Raboff, Pezzulo Giovanni

机构信息

Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.

Sapienza University of Rome, Roma, Lazio, Italy.

出版信息

R Soc Open Sci. 2025 Apr 9;12(4):241161. doi: 10.1098/rsos.241161. eCollection 2025 Apr.


DOI:10.1098/rsos.241161
PMID:40206860
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11978448/
Abstract

We humans are capable of solving challenging planning problems, but the range of adaptive strategies that we use to address them is not yet fully characterized. Here, we designed a series of problem-solving tasks that require planning at different depths. After systematically comparing the performance of participants and planning models, we found that when facing problems that require planning to a certain number of subgoals (from 1 to 8), participants make an adaptive use of their cognitive resources-namely, they tend to select an initial plan having the minimum required depth, rather than selecting the same depth for all problems. These results support the view of problem-solving as a bounded rational process, which adapts costly cognitive resources to task demands.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/d653f5deaaae/rsos.241161.f007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/d937574db964/rsos.241161.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/1116db59dfeb/rsos.241161.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/d88160aec19b/rsos.241161.f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/c32adf26c396/rsos.241161.f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/844ddf44ec6f/rsos.241161.f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/3e71e8f834b6/rsos.241161.f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/d653f5deaaae/rsos.241161.f007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/d937574db964/rsos.241161.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/1116db59dfeb/rsos.241161.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/d88160aec19b/rsos.241161.f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/c32adf26c396/rsos.241161.f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/844ddf44ec6f/rsos.241161.f005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/3e71e8f834b6/rsos.241161.f006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f9b5/11978448/d653f5deaaae/rsos.241161.f007.jpg

相似文献

[1]
Adaptive planning depth in human problem-solving.

R Soc Open Sci. 2025-4-9

[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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本文引用的文献

[1]
A recurrent network model of planning explains hippocampal replay and human behavior.

Nat Neurosci. 2024-7

[2]
Beyond simple laboratory studies: Developing sophisticated models to study rich behavior.

Phys Life Rev. 2023-9

[3]
Empowerment contributes to exploration behaviour in a creative video game.

Nat Hum Behav. 2023-9

[4]
Bounded rationality, enactive problem solving, and the neuroscience of social interaction.

Front Psychol. 2023-5-18

[5]
Expertise increases planning depth in human gameplay.

Nature. 2023-6

[6]
Humans account for cognitive costs when finding shortcuts: An information-theoretic analysis of navigation.

PLoS Comput Biol. 2023-1

[7]
Curriculum learning for human compositional generalization.

Proc Natl Acad Sci U S A. 2022-10-11

[8]
People construct simplified mental representations to plan.

Nature. 2022-6

[9]
Rational use of cognitive resources in human planning.

Nat Hum Behav. 2022-8

[10]
Entropy of city street networks linked to future spatial navigation ability.

Nature. 2022-4

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