## On the Amount of Nonconstructivity in Learning Formal Languages from Positive Data
(Manindra Agrawal and S. Barry Cooper and Ansheng Li, Eds.) Lecture Notes in Computer Science 7287, pp. 423--434, Springer 2012.
This paper studies the amount of nonconstructivity needed to learn classes of formal languages from positive data. Different learning types are compared with respect to the amount of nonconstructivity needed to learn indexable classes and recursively enumerable classes, respectively, of formal languages from positive data. Matching upper and lower bounds for the amount of nonconstructivity needed are shown.
This research was performed partially while the third author was visiting the Institute of Mathematical Sciences at the National University of Singapore in September 2011. His visit was supported by the Institute. Sanjay Jain was supported in part by NUS grant numbers C252-000-087-001 and R252-000-420-112, and Frank Stephan was supported in part by NUS grant number R252-000-420-112. ©Copyright 2012, Springer |