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An Attention-Driven Computational Model of Human Causal Reasoning

Bello, Paul; Lovett, Andrew; Briggs, Gordon; O'Neill, Kevin; (2018) An Attention-Driven Computational Model of Human Causal Reasoning. In: Proceedings of the 40th Annual Meeting of the Cognitive Science Society. (pp. pp. 1353-1358). Cognitive Science Society (CSS): Madison, USA. Green open access

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Abstract

Herein we describe CRAMM, a framework for Causal Reasoning via Attention and Mental Models. CRAMM develops and extends assumptions made by a previously developed counterfactual simulation model of human causal judgment. We implement CRAMM computationally and demonstrate how it robustly captures human causal judgments about simple two-object interactions at the level of underlying cognitive and perceptual processes, including data on eye-movements that serve as direct evidence for the role of counterfactuals in causal judgment.

Type: Proceedings paper
Title: An Attention-Driven Computational Model of Human Causal Reasoning
Event: CogSci 2018
Open access status: An open access version is available from UCL Discovery
Publisher version: https://escholarship.org/uc/item/7bw8d284
Language: English
Additional information: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: causal cognition; mental models; reasoning; attention; perception; cognitive architecture; computational model
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: https://discovery-pp.ucl.ac.uk/id/eprint/10197253
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