The ecological rationality of explanatory reasoning.
There is growing evidence that explanatory considerations influence how people change their degrees of belief in light of new information. Recent studies indicate that this influence is systematic and may result from people's following a probabilistic update rule. While formally very similar to Baye...
| Publicado en: | Studies in History & Philosophy of Science Part A Vol. 79; pp. 1 - 15 |
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| Formato: | Artículo |
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Elsevier B.V.
Feb2020
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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=hlh&AN=141754546&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 141754546 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00393681 HPS jtl: Studies in History & Philosophy of Science Part A issn: 00393681 maglogo: N pubinfo: dt: Feb2020 vid: 79 pid: 2410 pub: Elsevier B.V. artinfo: ui: 141754546 10.1016/j.shpsa.2019.06.004 ppf: 1 ppct: 14 formats: tig: atl: The ecological rationality of explanatory reasoning. aug: au: Douven, Igor affil: SND, CNRS, Sorbonne University, 1, rue Victor Cousin, 75005, Paris, France su: Reasoning Computer programming Philosophers Reasoning in children Computer simulation Human rights sug: subj: Reasoning Computer programming Philosophers Reasoning in children Computer simulation Human rights keyword: Agent-based optimization Belief updating Ecological rationality Explanation Inference Probability ab: There is growing evidence that explanatory considerations influence how people change their degrees of belief in light of new information. Recent studies indicate that this influence is systematic and may result from people's following a probabilistic update rule. While formally very similar to Bayes' rule, the rule or rules people appear to follow are different from, and inconsistent with, that better-known update rule. This raises the question of the normative status of those updating procedures. Is the role explanation plays in people's updating their degrees of belief a bias? Or are people right to update on the basis of explanatory considerations, in that this offers benefits that could not be had otherwise? Various philosophers have argued that any reasoning at deviance with Bayesian principles is to be rejected, and so explanatory reasoning, insofar as it deviates from Bayes' rule, can only be fallacious. We challenge this claim by showing how the kind of explanation-based update rules to which people seem to adhere make it easier to strike the best balance between being fast learners and being accurate learners. Borrowing from the literature on ecological rationality, we argue that what counts as the best balance is intrinsically context-sensitive, and that a main advantage of explanatory update rules is that, unlike Bayes' rule, they have an adjustable parameter which can be fine-tuned per context. The main methodology to be used is agent-based optimization, which also allows us to take an evolutionary perspective on explanatory reasoning. • Uses computer simulations to show the ecological rationality of explanatory reasoning. • Connects computational results on explanatory reasoning with empirical results from psychology. • Shows the standard arguments in favor of Bayesian updating to be flawed. • Links to computer code that readers can easily use to run their own simulations and thereby to make further comparisons between update rules. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2020 holdings: @attributes: islocal: N |
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