{"pk":31746,"title":"Rule Learning and the Power Law: A Computational Model and Empirical Results","subtitle":null,"abstract":"Using a process model of skill acquisition allo-\nwed us to examine the microstructure of subjects'\nperformance of a scheduling task. The model, im-\nplemented in the Soar-architecture, fits many qua-\nlitative (e.g., learning rate) and quantitative (e.g.,\nsolution time) effects found in previously collec-\nted data. T h e model's predictions were tested\nwith data from a new study where the identical\ntask was given to the model and to 14 subjects.\nAgain a general fitof the model was found with\nthe restrictions that the task is easier for the m o -\ndel than for subjects and its performance impro-\nves more quickly. T h e episodic memory chunks it\nlearns while scheduling tasks show h o w acquisition\nof general rules can be performed without resort\nto explicit declarative rule generation. T h e model\nalso provides an explanation of the noise typically\nfound when fittinga set of data to a power law —\nit is the result of chunking over actual knowledge\nrather than \"average\" knowledge. Only when the\ndata are averaged (over subjects here) does the\nsmooth power law appear.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Submitted Presentations","is_remote":true,"remote_url":"https://escholarship.org/uc/item/2r37330b","frozenauthors":[{"first_name":"Josef","middle_name":"","last_name":"Nerb","name_suffix":"","institution":"University of Regensburg","department":""},{"first_name":"Josef","middle_name":"F.","last_name":"Krems","name_suffix":"","institution":"University of Regensburg","department":""},{"first_name":"Frank","middle_name":"E .","last_name":"Ritter","name_suffix":"","institution":"University of Nottingham","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1993-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/31746/galley/22814/download/"}]}