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{
    "pk": 31691,
    "title": "A Model-based Approach to Learning from Attention-focusing Failures",
    "subtitle": null,
    "abstract": "In this paper we present a theory of how\nmachines can learn from attention focusing\nfailures. Our method requires that learning\nmechanisms have available a detailed model\nof decision-making mechanisms they are to\nmodify; it is therefore central to this research\nto develop and present such a model. The\nportions of our developing model presented\nbelow concern those parts of a decision-making\napparatus that should be approximately the\nsame & somone agent to another. Though\nlearning mechanisms would have to be sensitive\nto both the idiosyncratic and agent-invariant\nelements of aji cidaptable decision architecture,\nw e have concentrated on the invariant elements,\nwhich provide the most general constraints on\nlearning.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Submitted Presentations",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/1f58d9zg",
    "frozenauthors": [
        {
            "first_name": "Michael",
            "middle_name": "",
            "last_name": "Freed",
            "name_suffix": "",
            "institution": "Northwestern University",
            "department": ""
        },
        {
            "first_name": "Gregg",
            "middle_name": "",
            "last_name": "Collins",
            "name_suffix": "",
            "institution": "Northwestern University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1993-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/31691/galley/22759/download/"
        }
    ]
}