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An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems

We introduce and develop a method that demonstrates that the algorithmic information content of a system can be used as a steering handle in the dynamical phase space, thus affording an avenue for controlling and reprogramming systems. The method consists of applying a series of controlled intervent...

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Autores principales: Zenil, Hector, Kiani, Narsis A., Marabita, Francesco, Deng, Yue, Elias, Szabolcs, Schmidt, Angelika, Ball, Gordon, Tegnér, Jesper
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6831824/
https://www.ncbi.nlm.nih.gov/pubmed/31541920
http://dx.doi.org/10.1016/j.isci.2019.07.043
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author Zenil, Hector
Kiani, Narsis A.
Marabita, Francesco
Deng, Yue
Elias, Szabolcs
Schmidt, Angelika
Ball, Gordon
Tegnér, Jesper
author_facet Zenil, Hector
Kiani, Narsis A.
Marabita, Francesco
Deng, Yue
Elias, Szabolcs
Schmidt, Angelika
Ball, Gordon
Tegnér, Jesper
author_sort Zenil, Hector
collection PubMed
description We introduce and develop a method that demonstrates that the algorithmic information content of a system can be used as a steering handle in the dynamical phase space, thus affording an avenue for controlling and reprogramming systems. The method consists of applying a series of controlled interventions to a networked system while estimating how the algorithmic information content is affected. We demonstrate the method by reconstructing the phase space and their generative rules of some discrete dynamical systems (cellular automata) serving as controlled case studies. Next, the model-based interventional or causal calculus is evaluated and validated using (1) a huge large set of small graphs, (2) a number of larger networks with different topologies, and finally (3) biological networks derived from a widely studied and validated genetic network (E. coli) as well as on a significant number of differentiating (Th17) and differentiated human cells from a curated biological network data.
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spelling pubmed-68318242019-11-08 An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems Zenil, Hector Kiani, Narsis A. Marabita, Francesco Deng, Yue Elias, Szabolcs Schmidt, Angelika Ball, Gordon Tegnér, Jesper iScience Article We introduce and develop a method that demonstrates that the algorithmic information content of a system can be used as a steering handle in the dynamical phase space, thus affording an avenue for controlling and reprogramming systems. The method consists of applying a series of controlled interventions to a networked system while estimating how the algorithmic information content is affected. We demonstrate the method by reconstructing the phase space and their generative rules of some discrete dynamical systems (cellular automata) serving as controlled case studies. Next, the model-based interventional or causal calculus is evaluated and validated using (1) a huge large set of small graphs, (2) a number of larger networks with different topologies, and finally (3) biological networks derived from a widely studied and validated genetic network (E. coli) as well as on a significant number of differentiating (Th17) and differentiated human cells from a curated biological network data. Elsevier 2019-08-08 /pmc/articles/PMC6831824/ /pubmed/31541920 http://dx.doi.org/10.1016/j.isci.2019.07.043 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Zenil, Hector
Kiani, Narsis A.
Marabita, Francesco
Deng, Yue
Elias, Szabolcs
Schmidt, Angelika
Ball, Gordon
Tegnér, Jesper
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
title An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
title_full An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
title_fullStr An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
title_full_unstemmed An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
title_short An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
title_sort algorithmic information calculus for causal discovery and reprogramming systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6831824/
https://www.ncbi.nlm.nih.gov/pubmed/31541920
http://dx.doi.org/10.1016/j.isci.2019.07.043
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