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{
    "pk": 28053,
    "title": "How people detect incomplete explanations",
    "subtitle": null,
    "abstract": "In theory, there exists no bound to a causal explanation – every\nexplanation can be elaborated further. But reasoners rate some\nexplanations as more complete than others. To account for this\nbehavior, we developed a novel theory of the detection of\nexplanatory incompleteness. The theory is based on the idea\nthat reasoners construct mental models of causal explanations.\nBy default, each causal relation refers to a single mental model.\nReasoners should consider an explanation complete when they\ncan construct a single mental model, but incomplete when they\nmust consider multiple models. Reasoners should thus rate\ncausal chains, e.g., A causes B and B causes C, as more\ncomplete than “common cause” explanations (e.g., A causes B\nand A causes C) or “common effect” explanations (e.g., A\ncauses C and B causes C). Two experiments validate the\ntheory's prediction. The data suggest that reasoners construct\nmental models when generating explanations.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "explanatory reasoning"
        },
        {
            "word": "incompleteness"
        },
        {
            "word": "causal\nreasoning"
        },
        {
            "word": "mental models"
        }
    ],
    "section": "Publication-based-Talks",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/1vg5g5qc",
    "frozenauthors": [
        {
            "first_name": "Joanna",
            "middle_name": "",
            "last_name": "Korman",
            "name_suffix": "",
            "institution": "Navy Center for Applied Researcher in Artificial Intelligence",
            "department": ""
        },
        {
            "first_name": "Sangeet",
            "middle_name": "",
            "last_name": "Khemlani",
            "name_suffix": "",
            "institution": "Navy Center for Applied Researcher in Artificial Intelligence",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2018-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28053/galley/17692/download/"
        }
    ]
}