Parallel rewriting in neural networks

Ekaterina Komendantskaya

Parallel rewriting in neural networks

Ekaterina Komendantskaya

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Rewriting systems are used in various areas of computer science, and especially in lambda-calculus, higher-order logics and functional programming. We show that the unsupervised learning networks can implement parallel rewriting. We show how this general correspondence can be refined in order to perform parallel term rewriting in neural networks, for any given first-order term. We simulate these neural networks in the MATLAB Neural Network Toolbox and present the complete library of functions written in the MATLAB Neural Network Toolbox.

Original language	English
Title of host publication	IJCCI 2009: Proceedings of the International Joint Conference on Computational Intelligence
Editors	A Dourado, A Rosa, K Madani
Place of Publication	Setubal
Publisher	Institute for Systems and Technologies of Information, Control and Communication
Pages	452-458
Number of pages	7
ISBN (Print)	978-989-674-014-6
Publication status	Published - 2009
Event	1st International Joint Conference on Computational Intelligence - Funchal, Portugal Duration: 5 Oct 2009 → 7 Oct 2009

Conference

Conference	1st International Joint Conference on Computational Intelligence
Abbreviated title	IJCCI 2009
Country/Territory	Portugal
City	Funchal
Period	5/10/09 → 7/10/09

Keywords

Computational logic in neural networks
Neuro-symbolic networks
Abstract rewriting
Parallel term-rewriting
Unsupervised learning
Computer simulation of neural networks

Cite this

@inproceedings{68b3f7a6c8b2485fb1bdf5565d70b2c2,

title = "Parallel rewriting in neural networks",

abstract = "Rewriting systems are used in various areas of computer science, and especially in lambda-calculus, higher-order logics and functional programming. We show that the unsupervised learning networks can implement parallel rewriting. We show how this general correspondence can be refined in order to perform parallel term rewriting in neural networks, for any given first-order term. We simulate these neural networks in the MATLAB Neural Network Toolbox and present the complete library of functions written in the MATLAB Neural Network Toolbox.",

keywords = "Computational logic in neural networks, Neuro-symbolic networks, Abstract rewriting, Parallel term-rewriting, Unsupervised learning, Computer simulation of neural networks",

author = "Ekaterina Komendantskaya",

year = "2009",

language = "English",

isbn = "978-989-674-014-6",

pages = "452--458",

editor = "A Dourado and A Rosa and K Madani",

booktitle = "IJCCI 2009: Proceedings of the International Joint Conference on Computational Intelligence",

publisher = "Institute for Systems and Technologies of Information, Control and Communication",

note = "1st International Joint Conference on Computational Intelligence, IJCCI 2009 ; Conference date: 05-10-2009 Through 07-10-2009",

}

Komendantskaya, E 2009, Parallel rewriting in neural networks. in A Dourado, A Rosa & K Madani (eds), IJCCI 2009: Proceedings of the International Joint Conference on Computational Intelligence. Institute for Systems and Technologies of Information, Control and Communication, Setubal, pp. 452-458, 1st International Joint Conference on Computational Intelligence, Funchal, Portugal, 5/10/09.

Parallel rewriting in neural networks. / Komendantskaya, Ekaterina.
IJCCI 2009: Proceedings of the International Joint Conference on Computational Intelligence. ed. / A Dourado; A Rosa; K Madani. Setubal: Institute for Systems and Technologies of Information, Control and Communication, 2009. p. 452-458.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Parallel rewriting in neural networks

AU - Komendantskaya, Ekaterina

PY - 2009

Y1 - 2009

N2 - Rewriting systems are used in various areas of computer science, and especially in lambda-calculus, higher-order logics and functional programming. We show that the unsupervised learning networks can implement parallel rewriting. We show how this general correspondence can be refined in order to perform parallel term rewriting in neural networks, for any given first-order term. We simulate these neural networks in the MATLAB Neural Network Toolbox and present the complete library of functions written in the MATLAB Neural Network Toolbox.

AB - Rewriting systems are used in various areas of computer science, and especially in lambda-calculus, higher-order logics and functional programming. We show that the unsupervised learning networks can implement parallel rewriting. We show how this general correspondence can be refined in order to perform parallel term rewriting in neural networks, for any given first-order term. We simulate these neural networks in the MATLAB Neural Network Toolbox and present the complete library of functions written in the MATLAB Neural Network Toolbox.

KW - Computational logic in neural networks

KW - Neuro-symbolic networks

KW - Abstract rewriting

KW - Parallel term-rewriting

KW - Unsupervised learning

KW - Computer simulation of neural networks

M3 - Conference contribution

SN - 978-989-674-014-6

SP - 452

EP - 458

BT - IJCCI 2009: Proceedings of the International Joint Conference on Computational Intelligence

A2 - Dourado, A

A2 - Rosa, A

A2 - Madani, K

PB - Institute for Systems and Technologies of Information, Control and Communication

CY - Setubal

T2 - 1st International Joint Conference on Computational Intelligence

Y2 - 5 October 2009 through 7 October 2009

ER -

Parallel rewriting in neural networks

Abstract

Conference

Keywords

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