The ecological rationality of decision criteria.
Standard evolutionary game theory investigates the evolutionary fitness of alternative behaviors in a fixed and single decision problem. This paper instead focuses on decision criteria, rather than on simple behaviors, as the general behavioral rules under selection in the population: the evolutiona...
| Publicado en: | Synthese Vol. 198; no. 12; pp. 11241 - 11265 |
|---|---|
| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Dec2021
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=152624492&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 152624492 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Dec2021 vid: 198 iid: 12 pid: 237 pub: Springer Nature artinfo: ui: 152624492 10.1007/s11229-020-02785-y ppf: 11241 ppct: 24 formats: fmt: @attributes: type: P size: 1.1MB tig: atl: The ecological rationality of decision criteria. aug: au: Galeazzi, Paolo Galeazzi, Alessandro affil: University of Bayreuth, Bayreuth, Germany University of Copenhagen, CIBS, Copenhagen, Denmark University of Brescia, Brescia, Italy su: Monte Carlo method Biological fitness Statistical decision making Expected utility Evolutionary theories sug: subj: Monte Carlo method Biological fitness Statistical decision making Expected utility Evolutionary theories keyword: Decision criteria Ecological rationality Evolutionary selection Population games ab: Standard evolutionary game theory investigates the evolutionary fitness of alternative behaviors in a fixed and single decision problem. This paper instead focuses on decision criteria, rather than on simple behaviors, as the general behavioral rules under selection in the population: the evolutionary fitness of classic decision criteria for rational choice is analyzed through Monte Carlo simulations over various classes of decision problems. Overall, quantifying the uncertainty in a probabilistic way and maximizing expected utility turns out to be evolutionarily beneficial in general. Minimizing regret also finds some evolutionary justifications in our results, while maximin seems to be always disadvantaged by differential selection. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2021. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
|---|