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{ "pk": 29844, "title": "A memory-augmented neural network model of abstract sequential reasoning", "subtitle": null, "abstract": "A key aspect of human reasoning is the ability to recognize abstract patterns in sequential data and then use those patternsto make novel inferences. Capturing this capacity for abstract reasoning is a major challenge for neural network modelsof human cognition. We present a recurrent neural network model of abstract sequential reasoning that is augmented witha form of episodic memory. This memory system enables the network to accomplish a form of variable-binding that haslong been considered an important component of abstract reasoning. We evaluate the model using visually grounded,abstract sequential reasoning and pattern completion tasks, including a task based on relations commonly found in RavensProgressive Matrices.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [], "section": "Poster Session 2", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/38m243md", "frozenauthors": [ { "first_name": "Ishan", "middle_name": "", "last_name": "Sinha", "name_suffix": "", "institution": "Princeton University", "department": "" }, { "first_name": "Jonathan", "middle_name": "", "last_name": "Cohen", "name_suffix": "", "institution": "Princeton University", "department": "" }, { "first_name": "Taylor", "middle_name": "", "last_name": "Webb", "name_suffix": "", "institution": "University of California Los Angeles", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2020-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/29844/galley/19698/download/" } ] }