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{
    "pk": 30418,
    "title": "Learning Salience Anmong Featured Through Contingency in the CEL Framework",
    "subtitle": null,
    "abstract": "Determining which features in an environment are salient given a task, salience assignment, is a central problem in machine learning. A related phenomenon, contingency ( the conditions under which relative salience among environemental features is acquired), is central to learning and memory in animal psychology. This paper presents an analysis of a set of empirical data on contingency and an algorithm for the salience assignment problem. The algorithm presented is implmented in a working computer profram which interacts with a simulated environement to produce contingent asssociative learning corresponding to relevant behavioral data. The model also makes specific empirical predictions that can be experimentally tested.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Paper Session 2",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/3nf6668t",
    "frozenauthors": [
        {
            "first_name": "Richard",
            "middle_name": "H.",
            "last_name": "Granger",
            "name_suffix": "",
            "institution": "University of California, Irvine",
            "department": ""
        },
        {
            "first_name": "Jeffrey",
            "middle_name": "C.",
            "last_name": "Schlimmer",
            "name_suffix": "",
            "institution": "University of California, Irvine",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1985-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/30418/galley/20267/download/"
        }
    ]
}