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{
    "pk": 26174,
    "title": "Searching large hypothesis spaces by asking questions",
    "subtitle": null,
    "abstract": "One way people deal with uncertainty is by asking questions.A showcase of this ability is the classic 20 questions gamewhere a player asks questions in search of a secret object. Pre-vious studies using variants of this task have found that peopleare effective question-askers according to normative Bayesianmetrics such as expected information gain. However, so far,the studies amenable to mathematical modeling have used onlysmall sets of possible hypotheses that were provided explic-itly to participants, far from the unbounded hypothesis spacespeople often grapple with. Here, we study how people eval-uate the quality of questions in an unrestricted 20 Questionstask. We present a Bayesian model that utilizes a large data setof object-question pairs and expected information gain to se-lect questions. This model provides good predictions regardingpeople’s preferences and outperforms simpler alternatives.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [
        {
            "word": "Bayesian modeling; active learning"
        }
    ],
    "section": "Papers",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/0dz4648h",
    "frozenauthors": [
        {
            "first_name": "Alexander",
            "middle_name": "N.",
            "last_name": "Cohen",
            "name_suffix": "",
            "institution": "Hunter College High School",
            "department": ""
        },
        {
            "first_name": "Brenden",
            "middle_name": "M.",
            "last_name": "Lake",
            "name_suffix": "",
            "institution": "New York University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2016-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/26174/galley/15810/download/"
        }
    ]
}