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  1.  46
    A Computable Universe: Understanding and Exploring Nature as Computation.Hector Zenil - unknown
    A Computable Universe is a collection of papers discussing computation in nature and the nature of computation, a compilation of the views of the pioneers in the contemporary area of intellectual inquiry focused on computational and informational theories of the world. This volume is the definitive source of informational/computational views of the world, and of cutting-edge models of the universe, both digital and quantum, discussed from a philosophical perspective as well as in the greatest technical detail. The book discusses the (...)
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  2.  13
    Image Characterization and Classification by Physical Complexity.Hector Zenil, Jean‐Paul Delahaye & Cédric Gaucherel - 2012 - Complexity 17 (3):26-42.
  3.  11
    Empirical Encounters with Computational Irreducibility and Unpredictability.Hector Zenil, Fernando Soler-Toscano & Joost J. Joosten - 2012 - Minds and Machines 22 (3):149-165.
    The paper presents an exploration of conceptual issues that have arisen in the course of investigating speed-up and slowdown phenomena in small Turing machines, in particular results of a test that may spur experimental approaches to the notion of computational irreducibility. The test involves a systematic attempt to outrun the computation of a large number of small Turing machines (3 and 4 state, 2 symbol) by means of integer sequence prediction using a specialized function for that purpose. The experiment prompts (...)
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  4.  34
    What Is Nature-Like Computation? A Behavioural Approach and a Notion of Programmability.Hector Zenil - 2013 - Philosophy and Technology (3):1-23.
    The aim of this paper is to propose an alternative behavioural definition of computation (and of a computer) based simply on whether a system is capable of reacting to the environment—the input—as reflected in a measure of programmability. This definition is intended to have relevance beyond the realm of digital computers, particularly vis-à-vis natural systems. This will be done by using an extension of a phase transition coefficient previously defined in an attempt to characterise the dynamical behaviour of cellular automata (...)
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  5.  3
    A Behavioural Foundation for Natural Computing and a Programmability Test.Hector Zenil - 2013 - In Gordana Dodig-Crnkovic Raffaela Giovagnoli (ed.), Computing Nature. pp. 87--113.
  6.  33
    An Algorithmic Approach to Information and Meaning.Hector Zenil - unknown
    While it is legitimate to study ideas and concepts related to information in their broadest sense, that formal approaches properly belong in specific contexts is a fact that is too often ignored. That their use outside these contexts amounts to misuse or imprecise use cannot and should not be overlooked. This paper presents a framework based on algorithmic information theory for discussing concepts of relevance to information in philosophical contexts. Special attention will be paid to the intersection of syntactic and (...)
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  7.  11
    Towards a Stable Definition of Program-Size Complexity.Hector Zenil - unknown
    We propose a test based on the theory of algorithmic complexity and an experimental evaluation of Levin's universal distribution to identify evidence in support of or in contravention of the claim that the world is algorithmic in nature. To this end statistical comparisons are undertaken of the frequency distributions of data from physical sources--repositories of information such as images, data stored in a hard drive, computer programs and DNA sequences--and the output frequency distributions generated by purely algorithmic means--by running abstract (...)
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  8.  13
    The World is Either Algorithmic or Mostly Random.Hector Zenil - unknown
    I will propose the notion that the universe is digital, not as a claim about what the universe is made of but rather about the way it unfolds. Central to the argument will be the concepts of symmetry breaking and algorithmic probability, which will be used as tools to compare the way patterns are distributed in our world to the way patterns are distributed in a simulated digital one. These concepts will provide a framework for a discussion of the informational (...)
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  9.  10
    On the Kolmogorov-Chaitin Complexity for Short Sequences.Hector Zenil - unknown
    This is a presentation about joint work between Hector Zenil and Jean-Paul Delahaye. Zenil presents Experimental Algorithmic Theory as Algorithmic Information Theory and NKS, put together in a mixer. Algorithmic Complexity Theory defines the algorithmic complexity k(s) as the length of the shortest program that produces s. But since finding this short program is in general an undecidable question, the only way to approach k(s) is to use compression algorithms. He shows how to use the Compress function in Mathematica to (...)
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  10.  8
    Randomness Through Computation: Some Answers, More Questions.Hector Zenil - unknown
    The book is intended to explain the larger and intuitive concept of randomness by means of computation, particularly through algorithmic complexity and recursion theory. It also includes the transcriptions (by A. German) of two panel discussion on the topics: Is The Universe Random?, held at the University of Vermont in 2007; and What is Computation? (How) Does Nature Compute?, held at the University of Indiana Bloomington in 2008. The book is intended to the general public, undergraduate and graduate students in (...)
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  11.  8
    On the Possible Computational Power of the Human Mind.Hector Zenil & Francisco Hernandez-Quiroz - 2007 - In Carlos Gershenson, Diederik Aerts & Bruce Edmonds (eds.), Worldviews, Science, and Us: Philosophy and Complexity. World Scientific. pp. 315--334.
  12.  1
    What Is Nature-Like Computation? A Behavioural Approach and a Notion of Programmability.Hector Zenil - 2014 - Philosophy and Technology 27 (3):399-421.
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  13.  3
    On the Dynamic Behaviour of Turing Universal Computing Systems.Hector Zenil - unknown
  14.  2
    Towards a Stable Definition of Algorithmic Randomness.Hector Zenil - unknown
    Although information content is invariant up to an additive constant, the range of possible additive constants applicable to programming languages is so large that in practice it plays a major role in the actual evaluation of K(s), the Kolmogorov complexity of a string s. We present a summary of the approach we've developed to overcome the problem by calculating its algorithmic probability and evaluating the algorithmic complexity via the coding theorem, thereby providing a stable framework for Kolmogorov complexity even for (...)
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  15.  2
    Program-Size Complexity for Short Strings.Hector Zenil - unknown
  16. A Computable Measure of Algorithmic Probability by Finite Approximations with an Application to Integer Sequences.Fernando Soler-Toscano & Hector Zenil - 2017 - Complexity:1-10.
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