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{ "pk": 29825, "title": "Configurative Weighting as a Two-Plane Approximation of Bayesian Estimates", "subtitle": null, "abstract": "Configurative weighting and adding can be a surprisingly effective approximation of multiplicative functions. In thecontext of joint probability judgment, Nilsson et al. (2009) has shown that, when marginal probabilities are only approxi-mately known, the configurative weighted average (CWA) of two probabilities not only predicts a high level of conjunctionfallacies, as observed in data, but also correlates higher with the true joint probability than if the two probabilities are mul-tiplied. Here we show that [1] the surface representing the optimal Bayesian estimate of a joint probability can be closelyapproximated by two planes, [2] configurative weighting and adding, such as the CWA model, constitutes such a two-planeapproximation, and [3] a bias-variance tradeoff is not sufficient to explain the accuracy of the CWA. More generally, thissuggests that the efficiency of heuristics might be due to suitable weighting operations rather than less-is-more effects.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [], "section": "Poster Session 2", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/8tr4d934", "frozenauthors": [ { "first_name": "Joakim", "middle_name": "", "last_name": "Sundh", "name_suffix": "", "institution": "University of Warwick", "department": "" }, { "first_name": "Jerker", "middle_name": "", "last_name": "Denrell", "name_suffix": "", "institution": "University of Warwick", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2020-01-01T21:00:00+03:00", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/29825/galley/19679/download/" } ] }