LEARNING OF RECOGNIZABLE PICTURE LANGUAGES
Rani Siromoney, Lisa Mathew, K.G. SUBRAMANIAN, Vincent Rajkumar Dare · International Journal of Pattern Recognition and Artificial Intelligence · 1994
Learning of certain classes of two-dimensional picture languages is considered in this paper. Linear time algorithms that learn in the limit, from positive data the classes of local picture languages and locally testable picture languages are presented. A crucial step for obtaining the learning algorithm for local picture languages is an explicit construction of a two-dimensional on-line tessellation acceptor for a given local picture language. A polynomial time algorithm that learns the class of recognizable picture languages from positive data and restricted subset queries, is presented in contrast to the fact that this class is not learnable in the limit from positive data alone.