Simple Recurrent Networks Learn Context-Free and Context-Sensitive Languages by Counting

DOI10.1162/089976601750399326zbMath1051.68555OpenAlexW2116723809WikidataQ43470790 ScholiaQ43470790MaRDI QIDQ2784810

Paul Rodriguez

Publication date: 2001

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/089976601750399326

zbMATH Keywords

Recurrent Neural Network

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (6)

An experimental unification of reservoir computing methods ⋮ Elman Backpropagation as Reinforcement for Simple Recurrent Networks ⋮ Stack-like and queue-like dynamics in recurrent neural networks ⋮ Stability analysis of reservoir computers dynamics via Lyapunov functions ⋮ Extracting symbolic knowledge from recurrent neural networks -- a fuzzy logic approach ⋮ Learning Nonregular Languages: A Comparison of Simple Recurrent Networks and LSTM

Cites Work

• Dynamical recognizers: real-time language recognition by analog computers
• On the computational power of neural nets
• The dynamic universality of sigmoidal neural networks
• Inference of Reversible Languages

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