{"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/"}]}