Article Instance

HTTP 200 OK
Allow: GET
Content-Type: application/json
Vary: Accept

{
    "pk": 32736,
    "title": "Rule learning by Habituation can be Simulated in Neural Networks",
    "subtitle": null,
    "abstract": "Contrary to a recent claim that neural network models are unable to account for data on infant habituation to artificial language sentences, the present simulations show successful coverage with cascade-correlation networks using analog encoding. The results demonstrate that a symbolic rule-based account is not required by the infant data.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Long Papers",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/94b313rf",
    "frozenauthors": [
        {
            "first_name": "Thomas",
            "middle_name": "R.",
            "last_name": "Shultz",
            "name_suffix": "",
            "institution": "Department of Psychology; McGill University",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1999-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/32736/galley/23798/download/"
        }
    ]
}