Noise-robust realization of Turing-complete cellular automata by using neural networks with pattern representation

DOI10.1016/J.PHYSLETA.2010.10.024zbMath1238.82020OpenAlexW1995643596MaRDI QIDQ418663

Makito Oku, Kazuyuki Aihara

Publication date: 29 May 2012

Published in: Physics Letters. A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physleta.2010.10.024

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) Cellular automata (computational aspects) (68Q80) Memory and learning in psychology (91E40) Neural nets and related approaches to inference from stochastic processes (62M45) Exactly solvable dynamic models in time-dependent statistical mechanics (82C23)

Related Items (1)

An RNA-based theory of natural universal computation

Cites Work

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• Associative dynamics in a chaotic neural network.
• On the computational power of neural nets
• Automata Studies. (AM-34)
• Statistical mechanics of cellular automata
• Neural networks and physical systems with emergent collective computational abilities.
• Learning representations by back-propagating errors
• A logical calculus of the ideas immanent in nervous activity

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