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{
    "pk": 32865,
    "title": "Learning, Memory, and Search in Planning",
    "subtitle": null,
    "abstract": "This paper describes D^DALUS, a system that uses a variant of means-ends analysis to generate plans and uses an incremental learning algorithm to acquire probabilistic search heuristics from problem solutions. W e summarize DjEDALUS' approach to search, knowledge, organization, and learning, and examine its behavior on multi-column subtraction. W e then evaluate the system in terms of its consistency with known results on human problem solving, comparing it to other psychological models of learntng and planning.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Paper Presentations -- Problem Solving and Transfer",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/1f49r40x",
    "frozenauthors": [
        {
            "first_name": "Pat",
            "middle_name": "",
            "last_name": "Langley",
            "name_suffix": "",
            "institution": "NASA Ames Research Center",
            "department": ""
        },
        {
            "first_name": "John",
            "middle_name": "A.",
            "last_name": "Allen",
            "name_suffix": "",
            "institution": "NASA Ames Research Center",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1991-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/32865/galley/23925/download/"
        }
    ]
}