{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T06:30:33Z","timestamp":1781245833763,"version":"3.54.1"},"reference-count":46,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000925","name":"John Templeton Foundation","doi-asserted-by":"publisher","award":["61454"],"award-info":[{"award-number":["61454"]}],"id":[{"id":"10.13039\/100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","award":["FA 9550-18-1-0077"],"award-info":[{"award-number":["FA 9550-18-1-0077"]}],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000183","name":"Army Research Office","doi-asserted-by":"publisher","award":["ARO W911NF-16-1-0474"],"award-info":[{"award-number":["ARO W911NF-16-1-0474"]}],"id":[{"id":"10.13039\/100000183","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Human behavior emerges from planning over elaborate decompositions of tasks into goals, subgoals, and low-level actions. How are these decompositions created and used? Here, we propose and evaluate a normative framework for task decomposition based on the simple idea that people decompose tasks to reduce the overall cost of planning while maintaining task performance. Analyzing 11,117 distinct graph-structured planning tasks, we find that our framework justifies several existing heuristics for task decomposition and makes predictions that can be distinguished from two alternative normative accounts. We report a behavioral study of task decomposition (<jats:italic>N<\/jats:italic> = 806) that uses 30 randomly sampled graphs, a larger and more diverse set than that of any previous behavioral study on this topic. We find that human responses are more consistent with our framework for task decomposition than alternative normative accounts and are most consistent with a heuristic\u2014betweenness centrality\u2014that is justified by our approach. Taken together, our results suggest the computational cost of planning is a key principle guiding the intelligent structuring of goal-directed behavior.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1011087","type":"journal-article","created":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T17:22:26Z","timestamp":1685640146000},"page":"e1011087","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":34,"title":["Humans decompose tasks by trading off utility and computational cost"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9138-7818","authenticated-orcid":true,"given":"Carlos G.","family":"Correa","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark K.","family":"Ho","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frederick","family":"Callaway","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathaniel D.","family":"Daw","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas L.","family":"Griffiths","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2023,6,1]]},"reference":[{"issue":"3","key":"pcbi.1011087.ref001","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.cognition.2008.08.011","article-title":"Hierarchically organized behavior and its neural foundations: a reinforcement learning perspective","volume":"113","author":"MM Botvinick","year":"2009","journal-title":"Cognition"},{"issue":"47","key":"pcbi.1011087.ref002","doi-asserted-by":"crossref","first-page":"29381","DOI":"10.1073\/pnas.1912330117","article-title":"Computational evidence for hierarchically structured reinforcement learning in humans","volume":"117","author":"MK Eckstein","year":"2020","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"4","key":"pcbi.1011087.ref003","doi-asserted-by":"crossref","first-page":"893","DOI":"10.1016\/j.neuron.2016.03.037","article-title":"Neural Mechanisms of Hierarchical Planning in a Virtual Subway Network","volume":"90","author":"J Balaguer","year":"2016","journal-title":"Neuron"},{"issue":"45","key":"pcbi.1011087.ref004","doi-asserted-by":"crossref","first-page":"13817","DOI":"10.1073\/pnas.1506367112","article-title":"Habitual control of goal selection in humans","volume":"112","author":"F Cushman","year":"2015","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"11","key":"pcbi.1011087.ref005","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1038\/nn.4650","article-title":"The hippocampus as a predictive map","volume":"20","author":"KL Stachenfeld","year":"2017","journal-title":"Nature Neuroscience"},{"issue":"1","key":"pcbi.1011087.ref006","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1037\/a0030852","article-title":"Cognitive control over learning: Creating, clustering, and generalizing task-set structure","volume":"120","author":"AGE Collins","year":"2013","journal-title":"Psychological Review"},{"issue":"4","key":"pcbi.1011087.ref007","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pcbi.1007594","article-title":"Discovery of hierarchical representations for efficient planning","volume":"16","author":"MS Tomov","year":"2020","journal-title":"PLOS Computational Biology"},{"issue":"8","key":"pcbi.1011087.ref008","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pcbi.1003779","article-title":"Optimal Behavioral Hierarchy","volume":"10","author":"A Solway","year":"2014","journal-title":"PLOS Computational Biology"},{"issue":"2","key":"pcbi.1011087.ref009","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1111\/tops.12086","article-title":"Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility Maximization","volume":"6","author":"RL Lewis","year":"2014","journal-title":"Topics in Cognitive Science"},{"issue":"6245","key":"pcbi.1011087.ref010","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1126\/science.aac6076","article-title":"Computational rationality: A converging paradigm for intelligence in brains, minds, and machines","volume":"349","author":"SJ Gershman","year":"2015","journal-title":"Science"},{"issue":"2","key":"pcbi.1011087.ref011","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1111\/tops.12142","article-title":"Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic","volume":"7","author":"TL Griffiths","year":"2015","journal-title":"Topics in Cognitive Science"},{"key":"pcbi.1011087.ref012","unstructured":"Correa CG, Ho MK, Callaway F, Griffiths TL. 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