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dc.contributor.authorZhang, Ruixun
dc.contributor.authorBrennan, Thomas J.
dc.contributor.authorLo, Andrew W.
dc.date.accessioned2014-12-23T20:52:29Z
dc.date.available2014-12-23T20:52:29Z
dc.date.issued2014-10
dc.date.submitted2014-07
dc.identifier.issn1932-6203
dc.identifier.urihttp://hdl.handle.net/1721.1/92488
dc.description.abstractDespite many compelling applications in economics, sociobiology, and evolutionary psychology, group selection is still one of the most hotly contested ideas in evolutionary biology. Here we propose a simple evolutionary model of behavior and show that what appears to be group selection may, in fact, simply be the consequence of natural selection occurring in stochastic environments with reproductive risks that are correlated across individuals. Those individuals with highly correlated risks will appear to form “groups”, even if their actions are, in fact, totally autonomous, mindless, and, prior to selection, uniformly randomly distributed in the population. This framework implies that a separate theory of group selection is not strictly necessary to explain observed phenomena such as altruism and cooperation. At the same time, it shows that the notion of group selection does captures a unique aspect of evolution—selection with correlated reproductive risk–that may be sufficiently widespread to warrant a separate term for the phenomenon.en_US
dc.description.sponsorshipMIT Laboratory for Financial Engineeringen_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pone.0110848en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourcePublic Library of Scienceen_US
dc.titleGroup Selection as Behavioral Adaptation to Systematic Risken_US
dc.typeArticleen_US
dc.identifier.citationZhang, Ruixun, Thomas J. Brennan, and Andrew W. Lo. “Group Selection as Behavioral Adaptation to Systematic Risk.” Edited by Claude Wicker-Thomas. PLoS ONE 9, no. 10 (October 29, 2014): e110848.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mathematicsen_US
dc.contributor.departmentSloan School of Managementen_US
dc.contributor.mitauthorZhang, Ruixunen_US
dc.contributor.mitauthorLo, Andrew W.en_US
dc.relation.journalPLoS ONEen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsZhang, Ruixun; Brennan, Thomas J.; Lo, Andrew W.en_US
dc.identifier.orcidhttps://orcid.org/0000-0002-6908-4236
dc.identifier.orcidhttps://orcid.org/0000-0003-2944-7773
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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