Learning the opportunity cost of time in a patch-foraging task.
Although most decision research concerns choice between simultaneously presented options, in many situations options are encountered serially, and the decision is whether to exploit an option or search for a better one. Such problems have a rich history in animal foraging, but we know little about t...
| Publicado en: | Cognitive, Affective & Behavioral Neuroscience Vol. 15; no. 4; pp. 837 - 854 |
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| Autores principales: | , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Dec2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=110839620&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110839620 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15307026 NA4 jtl: Cognitive, Affective & Behavioral Neuroscience issn: 15307026 maglogo: N pubinfo: dt: Dec2015 vid: 15 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 110839620 10.3758/s13415-015-0350-y 110839620 ppf: 837 ppct: 17 formats: fmt: @attributes: type: P tig: atl: Learning the opportunity cost of time in a patch-foraging task. aug: au: Constantino, Sara Daw, Nathaniel affil: Department of Psychology, New York University, 8th floor, 6 Washington Place New York 10003 USA sug: ab: Although most decision research concerns choice between simultaneously presented options, in many situations options are encountered serially, and the decision is whether to exploit an option or search for a better one. Such problems have a rich history in animal foraging, but we know little about the psychological processes involved. In particular, it is unknown whether learning in these problems is supported by the well-studied neurocomputational mechanisms involved in more conventional tasks. We investigated how humans learn in a foraging task, which requires deciding whether to harvest a depleting resource or switch to a replenished one. The optimal choice (given by the marginal value theorem; MVT) requires comparing the immediate return from harvesting to the opportunity cost of time, which is given by the long-run average reward. In two experiments, we varied opportunity cost across blocks, and subjects adjusted their behavior to blockwise changes in environmental characteristics. We examined how subjects learned their choice strategies by comparing choice adjustments to a learning rule suggested by the MVT (in which the opportunity cost threshold is estimated as an average over previous rewards) and to the predominant incremental-learning theory in neuroscience, temporal-difference learning (TD). Trial-by-trial decisions were explained better by the MVT threshold-learning rule. These findings expand on the foraging literature, which has focused on steady-state behavior, by elucidating a computational mechanism for learning in switching tasks that is distinct from those used in traditional tasks, and suggest connections to research on average reward rates in other domains of neuroscience. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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