By assuming that the Un iverse is best described as a cellular automaton, and by making use of some of the results from the field of computational mechanics, this paper discusses the extension of the notion of existence from a simple binary opposition to that of a continuum. It is argued that none of the traditional objects of science, or any objects from any discipline formal or not, can be said to be real in any absolute sense though a substantial realism may be associated with them. By problematising existence it is proposed that an evolutionary philosophy referred to as critical pluralism is more sensitive to the demands of complexity than contemporary scientific thought.

Abstract. We consider random boolean cellular automata on the integer lattice, i.e., the cells are identified with the integers from 1 to N. The behaviour of the automaton is mainly determined by the support of the random variable that selects one of the sixteen possible Boolean rules, independently for each cell. A cell is said to stabilize if it will not change its state anymore after some time. We classify the random boolean automata according to the positivity of their probability of stabilization. Here is an example of a consequence of our results: if the support contains at least 5 rules, then asymptotically as N tends to infinity the probability of stabilization is positive, whereas there exist random boolean cellular automata with 4 rules in their support for which this probability tends to 0. 1.

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

Abstract. Throughout nature, decentralized components emerge into complex forms. It is through their interaction that components, governed by simple rules, self-assemble to create specific entities. The programs constituting these entities are based on the rules present in a given system and are executed on the physically and chemically encoded information comprising the components and their environment. A threelevel approach is presented here which encompasses specifying a set of rules, modeling these rules to determine the outcome of a specific system in software, and translating to a physical system based on the set of rules present. The benefit of this approach is that no knowledge of the end result is required to create the physical system, mirroring the bottom-up process in nature. Five experiments, based on an example implementation of this approach, show that the translated physical systems self-assemble into the desired entities achieved by the simulations. These successful results demonstrate how this three-level approach is used for mapping virtual self-assembly rules to physical systems. 1

General System Theory concept is close to theory of control systems. In this chapter, we try to find a systematic view of complexity from the viewpoint of system concepts. The first part of the chapter covers about General System Theory from Bertalanffy’s book “General System Theory ” [1]. In this book he shows that reductionism is completely wrong and modelling the system from the holistic viewpoint is the correct approach. One approach to looking at complex systems in a systemic perspective and a way to control the emerging patterns as well is demonstrated. 14.1 General System Theory “System Theory ” represents a novel paradigm in scientific thinking [1]. General system theory is similar to “theory of evolution”, which comprises about everything between fossils digging, anatomy and the mathematical theory of selection, or behavior theory extending from bird watching to sophisticated

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This paper reports on a user study of a computer-aided learning environment for Materials Science. “MaterialSim ” is an agentbased set of microworlds built in the NetLogo modeling environment, for investigating crystallization, solidification, metallic grain growth and annealing. Six undergraduate students enrolled in an introductory Materials Science course participated in the study, in which they could run experiments and build models. The rationale for the design is that the agent-based perspective may foster deeper understanding of the relevant scientific phenomena. A core feature is that students can apply a small number of local rules to capture fundamental causality structures underlying complex behaviors within a domain. We present evidence in the form of excerpts and samples of students’ work, which demonstrates that experience with MaterialSim enabled them to identify and understand some of the unifying

For the sequence defined by a(n) = a(n − 1) + gcd(n, a(n − 1)) with a(1) = 7 we prove that a(n) − a(n − 1) takes on only 1’s and primes, making this recurrence a rare “naturally occurring ” generator of primes. Toward a generalization of this result to an arbitrary initial condition, we also study the limiting behavior of a(n)/n and a transience property of the evolution. 1

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Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation ’ and ‘information processing ’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism and connectionism/computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates ’ empirical aspects.