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{
    "pk": 30475,
    "title": "A Layered Network Model for Learning-to-learn and Configuration in Classical Conditioning",
    "subtitle": null,
    "abstract": "Networks composed of layers of adaptive elements provide a\nrigorous explanation for complex associative learning\nphenomena. In particular, a network composed of three\nadaptive elements can explain previously intractable\nphenomena, namely the rapid rate of reacquisitions,\nlearning-to-learn, spontaneous configuration, and negative\npatterning (the exclusive-OR problem). This paper will\ncompare the results of computer simulations to the\nbehavioral results of classical conditioning experiments\nusing the rabbit's nictitating membrane response.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Presented Papers",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/7815x1vw",
    "frozenauthors": [
        {
            "first_name": "E.",
            "middle_name": "James",
            "last_name": "Kehoe",
            "name_suffix": "",
            "institution": "University of New South Wales",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1986-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/30475/galley/20324/download/"
        }
    ]
}