47 found
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  1. Complexity and Information: Measuring Emergence, Self‐Organization, and Homeostasis at Multiple Scales.Carlos Gershenson & Nelson Fernández - 2013 - Complexity 18 (2):29-44.
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  2.  6
    Complexity Measurement of Natural and Artificial Languages.Gerardo Febres, Klaus Jaffé & Carlos Gershenson - 2015 - Complexity 20 (6):25-48.
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  3.  18
    The Implications of Interactions for Science and Philosophy.Carlos Gershenson - 2013 - Foundations of Science 18 (4):781-790.
    Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions—which reductionism neglects—are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply nonreductionism, non-materialism, non-predictability, non-Platonism, and non-Nihilism. As alternatives to each of these, holism, informism, adaptation, contextuality, and meaningfulness are put forward, respectively. A worldview that includes interactions not only describes better our world, but can help to solve many open scientific, philosophical, and (...)
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  4.  6
    A Novel Antifragility Measure Based on Satisfaction and Its Application to Random and Biological Boolean Networks.Omar K. Pineda, Hyobin Kim & Carlos Gershenson - 2019 - Complexity 2019:1-10.
    Antifragility is a property from which systems are able to resist stress and furthermore benefit from it. Even though antifragile dynamics is found in various real-world complex systems where multiple subsystems interact with each other, the attribute has not been quantitatively explored yet in those complex systems which can be regarded as multilayer networks. Here we study how the multilayer structure affects the antifragility of the whole system. By comparing single-layer and multilayer Boolean networks based on our recently proposed antifragility (...)
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  5.  7
    When Slower is Faster.Carlos Gershenson & Dirk Helbing - 2016 - Complexity 21 (2):9-15.
  6.  17
    The Sigma Profile: A Formal Tool to Study Organization and its Evolution at Multiple Scales.Carlos Gershenson - 2011 - Complexity 16 (5):37-44.
    The σ profile is presented as a tool to analyze the organization of systems at different scales, and how this organization changes in time. Describing structures at different scales as goal‐oriented agents, one can define σ ∈ [0,1] (satisfaction) as the degree to which the goals of each agent at each scale have been met. σ reflects the organization degree at that scale. The σ profile of a system shows the satisfaction at different scales, with the possibility to study their (...)
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  7.  62
    How Can We Think the Complex?Carlos Gershenson & Francis Heylighen - 2004 - In [Book Chapter] (Unpublished).
    In this chapter we want to provide philosophical tools for understanding and reasoning about complex systems. Classical thinking, which is taught at most schools and universities, has several problems for coping with complexity. We review classical thinking and its drawbacks when dealing with complexity, for then presenting ways of thinking which allow the better understanding of complex systems. Examples illustrate the ideas presented. This chapter does not deal with specific tools and techniques for managing complex systems, but we try to (...)
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  8. [Book Chapter] (Unpublished).Carlos Gershenson & Francis Heylighen - 2004
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  9.  62
    Self‐Organizing Traffic Lights at Multiple‐Street Intersections.Carlos Gershenson & David A. Rosenblueth - 2012 - Complexity 17 (4):23-39.
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  10. Complexity and Philosophy.Francis Heylighen, Paul Cilliers & Carlos Gershenson - 2006 - In [Book Chapter] (in Press).
    The science of complexity is based on a new way of thinking that stands in sharp contrast to the philosophy underlying Newtonian science, which is based on reductionism, determinism, and objective knowledge. This paper reviews the historical development of this new world view, focusing on its philosophical foundations. Determinism was challenged by quantum mechanics and chaos theory. Systems theory replaced reductionism by a scientifically based holism. Cybernetics and postmodern social science showed that knowledge is intrinsically subjective. These developments are being (...)
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  11.  14
    Harnessing the Complexity of Education with Information Technology.Carlos Gershenson - 2015 - Complexity 20 (5):13-16.
  12.  4
    Boolean Networks and Their Applications in Science and Engineering.Jose C. Valverde, Henning S. Mortveit, Carlos Gershenson & Yongtang Shi - 2020 - Complexity 2020:1-3.
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  13.  18
    Collaborations: The Fourth Age of Research.Carlos Gershenson - 2014 - Complexity 19 (1):1-5.
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  14.  6
    Complexity at Large.Carlos Gershenson - 2014 - Complexity 19 (5):1-5.
  15.  9
    Trajectory Stability in the Traveling Salesman Problem.Sergio Sánchez, Germinal Cocho, Jorge Flores, Carlos Gershenson, Gerardo Iñiguez & Carlos Pineda - 2018 - Complexity 2018:1-8.
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  16.  11
    Complexity At Large.Carlos Gershenson - 2013 - Complexity 18 (5):1-4.
  17. Complexity at Large.Carlos Gershenson - 2014 - Complexity 20 (1):1-10.
  18.  9
    News Items.Carlos Gershenson - 2011 - Complexity 16 (5):1-6.
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  19.  5
    Complexity at Large.Carlos Gershenson - 2011 - Complexity 16 (6):1-4.
  20.  9
    News Items.Carlos Gershenson - 2010 - Complexity:NA-NA.
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  21.  37
    Living is Information Processing: From Molecules to Global Systems.Keith D. Farnsworth, John Nelson & Carlos Gershenson - 2013 - Acta Biotheoretica 61 (2):203-222.
    We extend the concept that life is an informational phenomenon, at every level of organisation, from molecules to the global ecological system. According to this thesis: living is information processing, in which memory is maintained by both molecular states and ecological states as well as the more obvious nucleic acid coding; this information processing has one overall function—to perpetuate itself; and the processing method is filtration of, and synthesis of, information at lower levels to appear at higher levels in complex (...)
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  22.  25
    News Items.Carlos Gershenson - 2013 - Complexity 18 (3):1-7.
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  23.  21
    Complexity at Large—19.2.Carlos Gershenson - 2014 - Complexity 19 (2):1-5.
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  24.  19
    Complexity at Large.Carlos Gershenson - 2013 - Complexity 18 (1):1-6.
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  25.  11
    Complexity at Large.Carlos Gershenson - 2016 - Complexity 21 (3):3-8.
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  26.  15
    Complexity at Large—March 2012.Carlos Gershenson - 2012 - Complexity 17 (4):1-4.
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  27.  14
    Learning, Social Intelligence and the Turing Test.Bruce Edmonds & Carlos Gershenson - 2012 - In S. Barry Cooper (ed.), How the World Computes. pp. 182--192.
  28.  9
    News Items.Carlos Gershenson - 2009 - Complexity:NA-NA.
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  29.  8
    Complexity at Large.Carlos Gershenson - 2011 - Complexity 16 (4):1-5.
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  30.  8
    Complexity at Large-21.2.Carlos Gershenson - 2016 - Complexity 21 (2):1-8.
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  31.  8
    Complexity at Large.Carlos Gershenson - 2016 - Complexity 21 (4):3-6.
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  32.  8
    Complexity at Large.Carlos Gershenson - 2010 - Complexity 16 (2):1-4.
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  33.  8
    News Items.Carlos Gershenson - 2012 - Complexity 17 (3):1-4.
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  34.  6
    Complexity at Large: News Items.Carlos Gershenson - 2016 - Complexity 21 (1):1-5.
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  35.  6
    Complexity at Large.Carlos Gershenson - 2010 - Complexity:n/a-n/a.
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  36.  6
    Complexity at Large.Carlos Gershenson - 2010 - Complexity 16 (1):1-5.
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  37.  6
    News Items.Carlos Gershenson - 2013 - Complexity 18 (4):1-11.
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  38.  8
    Complexity at Large—19.3.Carlos Gershenson - 2014 - Complexity 19 (3):1-6.
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  39.  5
    Complexity at Large.Carlos Gershenson - 2013 - Complexity 18 (6):1-6.
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  40.  3
    Complexity at Large.Carlos Gershenson - 2015 - Complexity 20 (3):1-7.
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  41.  3
    Complexity at Large-21.5.Carlos Gershenson - 2016 - Complexity 21 (5):5-10.
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  42.  4
    Complexity at Large-19.4.Carlos Gershenson - 2014 - Complexity 19 (4):1-9.
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  43.  2
    Complexity at Large.Carlos Gershenson - 2011 - Complexity 17 (1):1-4.
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  44.  2
    Complexity at Large.Carlos Gershenson - 2011 - Complexity 16 (3):1-5.
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  45.  1
    Complexity at Large.Carlos Gershenson - 2013 - Complexity 18 (2):1-4.
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  46. Complexity at Large.Carlos Gershenson - 2015 - Complexity 20 (4):1-5.
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  47. [Book Chapter] (in Press).Francis Heylighen, Paul Cilliers & Carlos Gershenson - 2006
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