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{
    "pk": 28629,
    "title": "Explaining intuitive difficulty judgments by modeling physical effort and risk",
    "subtitle": null,
    "abstract": "The ability to estimate task difficulty is critical for many real-world decisions such as setting appropriate goals for ourselvesor appreciating others’ accomplishments. Here we give a computational account of how humans judge the difficultyof a range of physical construction tasks (e.g., moving 10 loose blocks from their initial configuration to their targetconfiguration, such as a vertical tower) by quantifying two key factors that influence construction difficulty: physical effortand physical risk. Physical effort captures the minimal work needed to transport all objects to their final positions, and iscomputed using a hybrid task-and-motion planner. Physical risk corresponds to stability of the structure, and is computedusing noisy physics simulations to capture the costs for precision (e.g., attention, coordination, fine motor movements)required for success. We show that the full effort-risk model captures human estimates of difficulty and construction timebetter than either component alone. Preprint link https://arxiv.org/abs/1905.04445.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Papers with Oral Presentations",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/0hr316x2",
    "frozenauthors": [
        {
            "first_name": "Ilker",
            "middle_name": "",
            "last_name": "Yildirim",
            "name_suffix": "",
            "institution": "Massachusetts Institute of Technology",
            "department": ""
        },
        {
            "first_name": "Basil",
            "middle_name": "",
            "last_name": "Saeed",
            "name_suffix": "",
            "institution": "Massachusetts Institute of Technology",
            "department": ""
        },
        {
            "first_name": "Grace",
            "middle_name": "",
            "last_name": "Bennett-Pierre",
            "name_suffix": "",
            "institution": "Stanford University",
            "department": ""
        },
        {
            "first_name": "Tobias",
            "middle_name": "",
            "last_name": "Gerstenberg",
            "name_suffix": "",
            "institution": "Stanford University",
            "department": ""
        },
        {
            "first_name": "Josh",
            "middle_name": "",
            "last_name": "Tenenbaum",
            "name_suffix": "",
            "institution": "Massachusetts Institute of Technology",
            "department": ""
        },
        {
            "first_name": "Hyowon",
            "middle_name": "",
            "last_name": "Gweon",
            "name_suffix": "",
            "institution": "Stanford University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "2019-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28629/galley/18500/download/"
        }
    ]
}