Literature DB >> 21974667

Partial information decomposition as a spatiotemporal filter.

Benjamin Flecker1, Wesley Alford, John M Beggs, Paul L Williams, Randall D Beer.   

Abstract

Understanding the mechanisms of distributed computation in cellular automata requires techniques for characterizing the emergent structures that underlie information processing in such systems. Recently, techniques from information theory have been brought to bear on this problem. Building on this work, we utilize the new technique of partial information decomposition to show that previous information-theoretic measures can confound distinct sources of information. We then propose a new set of filters and demonstrate that they more cleanly separate out the background domains, particles, and collisions that are typically associated with information storage, transfer, and modification in cellular automata.

Mesh:

Year:  2011        PMID: 21974667     DOI: 10.1063/1.3638449

Source DB:  PubMed          Journal:  Chaos        ISSN: 1054-1500            Impact factor:   3.642


  3 in total

Review 1.  Synergy, redundancy, and multivariate information measures: an experimentalist's perspective.

Authors:  Nicholas Timme; Wesley Alford; Benjamin Flecker; John M Beggs
Journal:  J Comput Neurosci       Date:  2013-07-03       Impact factor: 1.621

2.  Estimating the Unique Information of Continuous Variables.

Authors:  Ari Pakman; Amin Nejatbakhsh; Dar Gilboa; Abdullah Makkeh; Luca Mazzucato; Michael Wibral; Elad Schneidman
Journal:  Adv Neural Inf Process Syst       Date:  2021-12

3.  Information Decomposition of Target Effects from Multi-Source Interactions: Perspectives on Previous, Current and Future Work.

Authors:  Joseph T Lizier; Nils Bertschinger; Jürgen Jost; Michael Wibral
Journal:  Entropy (Basel)       Date:  2018-04-23       Impact factor: 2.524

  3 in total

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