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{ "pk": 32943, "title": "Perception-mediated Learning and Reasoning in the CHILDLIKE System", "subtitle": null, "abstract": "Intelligent agents interacting with their environments combine information from several sense modalities and indulge in tasks that have components of perception, reasoning, learning and planning. Traditional AI systems focus on a single component. This paper highlights the importance of the integrated perceive-reason-act-learn loop, and describes a system designed to capture this loop. As a first step, it learns about simple objects, their qualities, and the words that name and describe them. The visual-linguistic associations formed serve as a bias in acquiring further knowledge about actions, which in turn aids the system in satisfying its internal needs (e.g., hunger, thirst, sleep, curiosity). Learning mechanisms that extract, aggregate, generate, de-generate and generalize build a hierarchical network (that serves as internal models of the environment) with which the system perceives and reasons.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [], "section": "Poster Presentations", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/20f5r9f5", "frozenauthors": [ { "first_name": "Ganesh", "middle_name": "", "last_name": "Mani", "name_suffix": "", "institution": "Universtiy of Wisconsin, Madison", "department": "" }, { "first_name": "Leonard", "middle_name": "", "last_name": "Uhr", "name_suffix": "", "institution": "Universtiy of Wisconsin, Madison", "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/32943/galley/24003/download/" } ] }