Skip navigation
Skip navigation

Learnability of probabilistic automata via oracles

Guttman, Omri; Vishwanathan, S; Williamson, Robert


Efficient learnability using the state merging algorithm is known for a subclass of probabilistic automata termed μ-distinguishable. In this paper, we prove that state merging algorithms can be extended to efficiently learn a larger class of automata. In

CollectionsANU Research Publications
Date published: 2005
Type: Conference paper
Source: Algorithmic Learning Theory: Proceedings of the 16th International Conference on Algorithmic Learning Theory (ALT-05) - LNAI 3734
DOI: 10.1007/11564089_15


File Description SizeFormat Image
01_Guttman_Learnability_of_probabilistic_2005.pdf194.4 kBAdobe PDF    Request a copy

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  20 July 2017/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator