{"pk":30253,"title":"Dynamic Construction Of Finite Aucomata\nFrom Examples Using Hlll-Cllmbing","subtitle":null,"abstract":"The problem addressed In this paper is heuristically-guided learning of finite automata from examples. Given positive sample strings and negative sample strings, a finite automaton is generated and incrementally refined to accept all positive samples but no negative samples. This paper describes some experiments in applying hillcllmblng to modify finite automata to accept a desired regular language. We show that many problems can be solved by this simple method.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Submitted Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/5x20328b","frozenauthors":[{"first_name":"Masaru","middle_name":"","last_name":"Tomlta","name_suffix":"","institution":"Carnegie-Mellon University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"1982-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/30253/galley/20107/download/"}]}