{"pk":33112,"title":"Learning to count without a counter : A case study of dynamics and activation landscapes in recurrent networks","subtitle":null,"abstract":"The broad context of this study is the investigation of the nature of computation in recurrent networks (RNs). The cur?rent study has two parts. The first is to show that a R N can solve a problem that we take to be of interest (a counting task), and the second is to use the solution as a platform for develop?ing a more general understanding of RN s as computational mechanisms. W e begin by presenting the empirical results of training RN s on the counting task. The task {a b ) is the sim?plest possible grammar that requires a PD A or counter A R N was trained to predict the deterministic elements in sequences of the form a\"b\" * where n=l to 12. After training, it general?ized to n=18. Contrary to our expectations, on analyzing the hidden unit dynamics, we find no evidence of units acting like counters. Instead, we find an oscillator W e then explore the possible range of behaviors of oscillators using iterated maps and in the second part of the paper we describe the use of iter?ated maps for understanding R N mechanisms in terms of \"activation landscapes\". This analysis leads to used an under?standing of the behavior of network generated in the simula?tion study.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"17","is_remote":true,"remote_url":"https://escholarship.org/uc/item/8mm1t679","frozenauthors":[{"first_name":"Janet","middle_name":"","last_name":"Wiles","name_suffix":"","institution":"University of Queensland","department":""},{"first_name":"Jeff","middle_name":"","last_name":"Elman","name_suffix":"","institution":"University of California, San Diego","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1995-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/33112/galley/24173/download/"}]}