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{
    "pk": 31246,
    "title": "Direct, Incremental Learning of Fuzzy Propositions",
    "subtitle": null,
    "abstract": "To enable the gradual learning of symbolic representations, a new fuzzy logical operator is developed that supports the expression of negation to degrees. As a result, simple fuzzy propositions become instantiable in a feedforward network having multiplicative nodes and tunable negation links. A backpropagation learning procedure has been straightforwardly developed for such a network and applied to effect the direct, incremental learning of fuzzy propositions in a natural and satisfying manner. Some results of this approach and comparisons to related approaches are discussed as well as directions for further extension.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Talks",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/8kh9c3tb",
    "frozenauthors": [
        {
            "first_name": "Gregg",
            "middle_name": "C.",
            "last_name": "Oden",
            "name_suffix": "",
            "institution": "University of Iowa",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1992-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/31246/galley/22315/download/"
        }
    ]
}