80 research outputs found

    Universal Cellular Automata and Class 4

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    Wolfram has provided a qualitative classification of cellular automata(CA) rules according to which, there exits a class of CA rules (called Class 4) which exhibit complex pattern formation and long-lived dynamical activity (long transients). These properties of Class 4 CA's has led to the conjecture that Class 4 rules are Universal Turing machines i.e. they are bases for computational universality. We describe an embedding of a ``small'' universal Turing machine due to Minsky, into a cellular automaton rule-table. This produces a collection of (k=18,r=1)(k=18,r=1) cellular automata, all of which are computationally universal. However, we observe that these rules are distributed amongst the various Wolfram classes. More precisely, we show that the identification of the Wolfram class depends crucially on the set of initial conditions used to simulate the given CA. This work, among others, indicates that a description of complex systems and information dynamics may need a new framework for non-equilibrium statistical mechanics.Comment: Latex, 10 pages, 5 figures uuencode

    Effect of Chaotic Noise on Multistable Systems

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    In a recent letter [Phys.Rev.Lett. {\bf 30}, 3269 (1995), chao-dyn/9510011], we reported that a macroscopic chaotic determinism emerges in a multistable system: the unidirectional motion of a dissipative particle subject to an apparently symmetric chaotic noise occurs even if the particle is in a spatially symmetric potential. In this paper, we study the global dynamics of a dissipative particle by investigating the barrier crossing probability of the particle between two basins of the multistable potential. We derive analytically an expression of the barrier crossing probability of the particle subject to a chaotic noise generated by a general piecewise linear map. We also show that the obtained analytical barrier crossing probability is applicable to a chaotic noise generated not only by a piecewise linear map with a uniform invariant density but also by a non-piecewise linear map with non-uniform invariant density. We claim, from the viewpoint of the noise induced motion in a multistable system, that chaotic noise is a first realization of the effect of {\em dynamical asymmetry} of general noise which induces the symmetry breaking dynamics.Comment: 14 pages, 9 figures, to appear in Phys.Rev.

    A Behavioural Foundation for Natural Computing and a Programmability Test

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    What does it mean to claim that a physical or natural system computes? One answer, endorsed here, is that computing is about programming a system to behave in different ways. This paper offers an account of what it means for a physical system to compute based on this notion. It proposes a behavioural characterisation of computing in terms of a measure of programmability, which reflects a system's ability to react to external stimuli. The proposed measure of programmability is useful for classifying computers in terms of the apparent algorithmic complexity of their evolution in time. I make some specific proposals in this connection and discuss this approach in the context of other behavioural approaches, notably Turing's test of machine intelligence. I also anticipate possible objections and consider the applicability of these proposals to the task of relating abstract computation to nature-like computation.Comment: 37 pages, 4 figures. Based on an invited Talk at the Symposium on Natural/Unconventional Computing and its Philosophical Significance, Alan Turing World Congress 2012, Birmingham, UK. http://link.springer.com/article/10.1007/s13347-012-0095-2 Ref. glitch fixed in 2nd. version; Philosophy & Technology (special issue on History and Philosophy of Computing), Springer, 201

    A framework for the local information dynamics of distributed computation in complex systems

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    The nature of distributed computation has often been described in terms of the component operations of universal computation: information storage, transfer and modification. We review the first complete framework that quantifies each of these individual information dynamics on a local scale within a system, and describes the manner in which they interact to create non-trivial computation where "the whole is greater than the sum of the parts". We describe the application of the framework to cellular automata, a simple yet powerful model of distributed computation. This is an important application, because the framework is the first to provide quantitative evidence for several important conjectures about distributed computation in cellular automata: that blinkers embody information storage, particles are information transfer agents, and particle collisions are information modification events. The framework is also shown to contrast the computations conducted by several well-known cellular automata, highlighting the importance of information coherence in complex computation. The results reviewed here provide important quantitative insights into the fundamental nature of distributed computation and the dynamics of complex systems, as well as impetus for the framework to be applied to the analysis and design of other systems.Comment: 44 pages, 8 figure

    25 Years of Self-organized Criticality: Concepts and Controversies

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    Introduced by the late Per Bak and his colleagues, self-organized criticality (SOC) has been one of the most stimulating concepts to come out of statistical mechanics and condensed matter theory in the last few decades, and has played a significant role in the development of complexity science. SOC, and more generally fractals and power laws, have attracted much comment, ranging from the very positive to the polemical. The other papers (Aschwanden et al. in Space Sci. Rev., 2014, this issue; McAteer et al. in Space Sci. Rev., 2015, this issue; Sharma et al. in Space Sci. Rev. 2015, in preparation) in this special issue showcase the considerable body of observations in solar, magnetospheric and fusion plasma inspired by the SOC idea, and expose the fertile role the new paradigm has played in approaches to modeling and understanding multiscale plasma instabilities. This very broad impact, and the necessary process of adapting a scientific hypothesis to the conditions of a given physical system, has meant that SOC as studied in these fields has sometimes differed significantly from the definition originally given by its creators. In Bak’s own field of theoretical physics there are significant observational and theoretical open questions, even 25 years on (Pruessner 2012). One aim of the present review is to address the dichotomy between the great reception SOC has received in some areas, and its shortcomings, as they became manifest in the controversies it triggered. Our article tries to clear up what we think are misunderstandings of SOC in fields more remote from its origins in statistical mechanics, condensed matter and dynamical systems by revisiting Bak, Tang and Wiesenfeld’s original papers

    Introduction to the artificial life issue

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    Artificial Life

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    Artificial Life contains a selection of articles from the first three issues of the journal of the same name, chosen so as to give an overview of the field, its connections with other disciplines, and its philosophical foundations. It is aimed at those with a general background in the sciences: some of the articles assume a mathematical background, or basic biology and computer science. I found it an informative and thought-provoking survey of a field around whose edges I have skirted for years. Many of the articles take biology as their starting point. Charles Taylor and David Jefferson provide a brief overview of the uses of artificial life as a tool in biology. Others look at more specific topics: Kristian Lindgren and Mats G. Nordahl use the iterated Prisoner's Dilemma to model cooperation and community structure in artificial ecosystems, Peter Schuster writes about molecular evolution in simplified test tube systems and its spin-off, evolutionary biotechnology, Przemyslaw Prusinkiewicz presents some examples of visual modelling of morphogenesis, illustrated with colour photographs, and Michael G. Dyer surveys different kinds of cooperative animal behaviour and some of the problems synthesising neural networks which exhibit similar behaviours. Other articles highlight the connections of artificial life with artificial intelligence. A review article by Luc Steels covers the relationship between the two fields, while another by Pattie Maes covers work on adaptive autonomous agents. Thomas S. Ray takes a synthetic approach to artificial life, with the goal of instantiating life rather than simulating it, he manages an awkward compromise between respecting the “physics and chemistry” of the digital medium and transplanting features of biological life. Kunihiko Kaneko looks to the mathematics of chaos theory to help understand the origins of complexity in evolution. In “Beyond Digital Naturalism”, Walter Fontana, Guenter Wagner and Leo Buss argue that the test of artificial life is to solve conceptual problems of biology and that “there exists a logical deep structure of which carbon chemistry-based life is a manifestation”, they use lambda calculus to try and build a theory of organisation.

    Artificial Life (proceedings)

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    Artificial Life (proceedings) All the pioneers from the 1988 workshop

    Artificial Life II (proceedings)

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    Artificial Life II (proceedings
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