CLJun 2, 2020
A Survey of Neural Networks and Formal Languages
arXiv:2006.01338v121 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental survey that synthesizes existing knowledge for researchers in machine learning and formal language theory.
The paper surveys the relationships between state-of-the-art neural network architectures and formal languages, focusing on their abilities to represent, recognize, and generate words from specific languages by learning from samples.
This report is a survey of the relationships between various state-of-the-art neural network architectures and formal languages as, for example, structured by the Chomsky Language Hierarchy. Of particular interest are the abilities of a neural architecture to represent, recognize and generate words from a specific language by learning from samples of the language.