{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T23:32:14Z","timestamp":1768433534305,"version":"3.49.0"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1012582","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T00:00:00Z","timestamp":1732233600000}}],"reference-count":50,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T00:00:00Z","timestamp":1731369600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100020769","name":"Center for Brains, Minds, and Machines, Massachusetts Institute of Technology","doi-asserted-by":"publisher","award":["CCF-1231216"],"award-info":[{"award-number":["CCF-1231216"]}],"id":[{"id":"10.13039\/100020769","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100011730","name":"Templeton World Charity Foundation","doi-asserted-by":"publisher","award":["TWCF0319"],"award-info":[{"award-number":["TWCF0319"]}],"id":[{"id":"10.13039\/501100011730","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017802","name":"Jacobs Family Foundation","doi-asserted-by":"publisher","award":["Fellowship"],"award-info":[{"award-number":["Fellowship"]}],"id":[{"id":"10.13039\/100017802","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>How people plan is an active area of research in cognitive science, neuroscience, and artificial intelligence. However, tasks traditionally used to study planning in the laboratory tend to be constrained to artificial environments, such as Chess and bandit problems. To date there is still no agreed-on model of how people plan in realistic contexts, such as navigation and search, where values intuitively derive from interactions between perception and cognition. To address this gap and move towards a more naturalistic study of planning, we present a novel spatial Maze Search Task (MST) where the costs and rewards are physically situated as distances and locations. We used this task in two behavioral experiments to evaluate and contrast multiple distinct computational models of planning, including optimal expected utility planning, several one-step heuristics inspired by studies of information search, and a family of planners that deviate from optimal planning, in which action values are estimated by the interactions between perception and cognition. We found that people\u2019s deviations from optimal expected utility are best explained by planners with a limited horizon, however our results do not exclude the possibility that in human planning action values may be also affected by cognitive mechanisms of numerosity and probability perception. This result makes a novel theoretical contribution in showing that limited planning horizon generalizes to spatial planning, and demonstrates the value of our multi-model approach for understanding cognition.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012582","type":"journal-article","created":{"date-parts":[[2024,11,12]],"date-time":"2024-11-12T18:36:17Z","timestamp":1731436577000},"page":"e1012582","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Approximate planning in spatial search"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2764-8611","authenticated-orcid":true,"given":"Marta","family":"Kryven","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suhyoun","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Max","family":"Kleiman-Weiner","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tomer","family":"Ullman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joshua","family":"Tenenbaum","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2024,11,12]]},"reference":[{"issue":"9","key":"pcbi.1012582.ref001","doi-asserted-by":"crossref","first-page":"e1004501","DOI":"10.1371\/journal.pcbi.1004501","article-title":"Prospective optimization with limited resources","volume":"11","author":"Joseph Snider","year":"2015","journal-title":"PLoS computational biology"},{"issue":"10","key":"pcbi.1012582.ref002","doi-asserted-by":"crossref","first-page":"3098","DOI":"10.1073\/pnas.1414219112","article-title":"Interplay of approximate planning strategies","volume":"112","author":"Quentin JM Huys","year":"2015","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"8","key":"pcbi.1012582.ref003","doi-asserted-by":"crossref","first-page":"1112","DOI":"10.1038\/s41562-022-01332-8","article-title":"Rational use of cognitive resources in human planning","volume":"6","author":"Frederick Callaway","year":"2022","journal-title":"Nature Human Behaviour"},{"issue":"45","key":"pcbi.1012582.ref004","doi-asserted-by":"crossref","first-page":"12868","DOI":"10.1073\/pnas.1609094113","article-title":"Adaptive integration of habits into depth-limited planning defines a habitual-goal\u2013directed spectrum","volume":"113","author":"Mehdi Keramati","year":"2016","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"pcbi.1012582.ref005","volume-title":"Theory of games and economic behavior","author":"John von Neumann","year":"1972"},{"key":"pcbi.1012582.ref006","unstructured":"Stuart J Russell and Peter Norvig. 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