Heuristics and optimal solutions to the breadth-depth dilemma

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• dc.contributor.author Moreno Bote, Rubén
• dc.contributor.author Ramírez Ruiz, Jorge
• dc.contributor.author Drugowitsch, Jan
• dc.contributor.author Hayden, Benjamin Y.
• dc.date.accessioned 2020-11-06T08:14:08Z
• dc.date.available 2020-11-06T08:14:08Z
• dc.date.issued 2020
• dc.description.abstract In multialternative risky choice, we are often faced with the opportunity to allocate our limited information-gathering capacity between several options before receiving feedback. In such cases, we face a natural trade-off between breadth—spreading our capacity across many options—and depth—gaining more information about a smaller number of options. Despite its broad relevance to daily life, including in many naturalistic foraging situations, the optimal strategy in the breadth–depth trade-off has not been delineated. Here, we formalize the breadth–depth dilemma through a finite-sample capacity model. We find that, if capacity is small (∼10 samples), it is optimal to draw one sample per alternative, favoring breadth. However, for larger capacities, a sharp transition is observed, and it becomes best to deeply sample a very small fraction of alternatives, which roughly decreases with the square root of capacity. Thus, ignoring most options, even when capacity is large enough to shallowly sample all of them, is a signature of optimal behavior. Our results also provide a rich casuistic for metareasoning in multialternative decisions with bounded capacity using close-to-optimal heuristics.en
• dc.description.sponsorship This work is supported by the HHMI (Grant 55008742), Ministry of Economic Affairs and Digital Transformation (Spain) (Grant BFU2017-85936-P), and Catalan Institution for Research and Advanced Studies–Academia (2016) to R.M.-B.; by NIH (Grant DA037229) to B.Y.H.; and by a scholar award from the James S. McDonnell Foundation (Grant 220020462) to J.D.
• dc.format.mimetype application/pdf
• dc.identifier.citation Moreno-Bote R, Ramírez-Ruiz J, Drugowitsch J, Hayden BY. Heuristics and optimal solutions to the breadth-depth dilemma. Proc Natl Acad Sci U S A. 2020 Aug 18;117(33):19799-808. DOI: 10.1073/pnas.2004929117
• dc.identifier.doi http://dx.doi.org/10.1073/pnas.2004929117
• dc.identifier.issn 0027-8424
• dc.identifier.uri http://hdl.handle.net/10230/45668
• dc.language.iso eng
• dc.publisher National Academy of Sciences
• dc.relation.ispartof Proceedings of the National Academy of Sciences of the United States of America. 2020 Aug 18;117(33):19799-808
• dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/BFU2017-85936-P
• dc.rights © 2020 the Author(s). Published by PNAS. This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND). https://creativecommons.org/licenses/by-nc-nd/4.0/
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
• dc.subject.keyword Decision makingen
• dc.subject.keyword Risky choiceen
• dc.subject.keyword Bounded rationalityen
• dc.subject.keyword Breadth–depth dilemmaen
• dc.subject.keyword Metareasoningen
• dc.title Heuristics and optimal solutions to the breadth-depth dilemmaen
• dc.type info:eu-repo/semantics/article
• dc.type.version info:eu-repo/semantics/publishedVersion