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Modeling Life as Cognitive Info-computation

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Language, Life, Limits (CiE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8493))

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Abstract

This article presents a naturalist approach to cognition understood as a network of info-computational, autopoietic processes in living systems. It provides a conceptual framework for the unified view of cognition as evolved from the simplest to the most complex organisms, based on new empirical and theoretical results. It addresses three fundamental questions: what cognition is, how cognition works and what cognition does at different levels of complexity of living organisms. By explicating the info-computational character of cognition, its evolution, agent-dependency and generative mechanisms we can better understand its life-sustaining and life-propagating role. The info-computational approach contributes to rethinking cognition as a process of natural computation in living beings that can be applied for cognitive computation in artificial systems.

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Author information

Authors and Affiliations

  1. School of Innovation, Design and Engineering, Mälardalen University, Västerås, Sweden

    Gordana Dodig-Crnkovic

Authors
  1. Gordana Dodig-Crnkovic
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Editor information

Editors and Affiliations

  1. College of Science, Department of Computer Science, Swansea University, SA2 8PP, Swansea, UK

    Arnold Beckmann

  2. Department of Algorithms and Their Applications, Eötvös Loránd University, Pázmány Péter sétány 1/c,, 1117, Budapest, Hungary

    Erzsébet Csuhaj-Varjú

  3. Computer Science Institute, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany

    Klaus Meer

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Dodig-Crnkovic, G. (2014). Modeling Life as Cognitive Info-computation. In: Beckmann, A., Csuhaj-Varjú, E., Meer, K. (eds) Language, Life, Limits. CiE 2014. Lecture Notes in Computer Science, vol 8493. Springer, Cham. https://doi.org/10.1007/978-3-319-08019-2_16

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  • DOI: https://doi.org/10.1007/978-3-319-08019-2_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08018-5

  • Online ISBN: 978-3-319-08019-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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