4,201 research outputs found

    Density Classification Quality of the Traffic-majority Rules

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    The density classification task is a famous problem in the theory of cellular automata. It is unsolvable for deterministic automata, but recently solutions for stochastic cellular automata have been found. One of them is a set of stochastic transition rules depending on a parameter η\eta, the traffic-majority rules. Here I derive a simplified model for these cellular automata. It is valid for a subset of the initial configurations and uses random walks and generating functions. I compare its prediction with computer simulations and show that it expresses recognition quality and time correctly for a large range of η\eta values.Comment: 40 pages, 9 figures. Accepted by the Journal of Cellular Automata. (Some typos corrected; the numbers for theorems, lemmas and definitions have changed with respect to version 1.

    On the Algorithmic Nature of the World

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    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 we have undertaken a statistical comparison of the frequency distributions of data from physical sources on the one hand--repositories of information such as images, data stored in a hard drive, computer programs and DNA sequences--and the frequency distributions generated by purely algorithmic means on the other--by running abstract computing devices such as Turing machines, cellular automata and Post Tag systems. Statistical correlations were found and their significance measured.Comment: Book chapter in Gordana Dodig-Crnkovic and Mark Burgin (eds.) Information and Computation by World Scientific, 2010. (http://www.idt.mdh.se/ECAP-2005/INFOCOMPBOOK/). Paper website: http://www.mathrix.org/experimentalAIT

    Empirical Encounters with Computational Irreducibility and Unpredictability

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    There are several forms of irreducibility in computing systems, ranging from undecidability to intractability to nonlinearity. This paper is an exploration of the conceptual issues that have arisen in the course of investigating speed-up and slowdown phenomena in small Turing machines. We present the 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 (all 3 and 4 state, 2 symbol) by means of integer sequence prediction using a specialized function finder program. This massive experiment prompts an investigation into rates of convergence of decision procedures and the decidability of sets in addition to a discussion of the (un)predictability of deterministic computing systems in practice. We think this investigation constitutes a novel approach to the discussion of an epistemological question in the context of a computer simulation, and thus represents an interesting exploration at the boundary between philosophical concerns and computational experiments.Comment: 18 pages, 4 figure

    Flexible RNA design under structure and sequence constraints using formal languages

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    The problem of RNA secondary structure design (also called inverse folding) is the following: given a target secondary structure, one aims to create a sequence that folds into, or is compatible with, a given structure. In several practical applications in biology, additional constraints must be taken into account, such as the presence/absence of regulatory motifs, either at a specific location or anywhere in the sequence. In this study, we investigate the design of RNA sequences from their targeted secondary structure, given these additional sequence constraints. To this purpose, we develop a general framework based on concepts of language theory, namely context-free grammars and finite automata. We efficiently combine a comprehensive set of constraints into a unifying context-free grammar of moderate size. From there, we use generic generic algorithms to perform a (weighted) random generation, or an exhaustive enumeration, of candidate sequences. The resulting method, whose complexity scales linearly with the length of the RNA, was implemented as a standalone program. The resulting software was embedded into a publicly available dedicated web server. The applicability demonstrated of the method on a concrete case study dedicated to Exon Splicing Enhancers, in which our approach was successfully used in the design of \emph{in vitro} experiments.Comment: ACM BCB 2013 - ACM Conference on Bioinformatics, Computational Biology and Biomedical Informatics (2013

    Новый генератор псевдослучайных последовательностей чисел на основе клеточного автомата

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    Розглядається новий генератор псевдовипадкових послідовностей біт, який реалізований на клітинному автоматі. Представлена апаратна реалізація генератора і виконано його програмне моделювання. За допомогою програмної моделі проведене тестування розробленого генератора псевдовипадкових чисел. Використані тести показали позитивний результат, який підтверджує високі статистичні властивості сформованої випадкової послідовності.This paper considers a novel pseudo-random bit sequence generator, which is implemented on a cellular automaton. It presents the hardware implementation of the generator and it the software simulation. With the help of the software model is testing of the random number generator was conducted. Tests showed a positive result, which confirms the high statistical properties of the generated random sequence.Рассматривается новый генератор псевдослучайных последовательностей бит, который реализован на клеточном автомате. Представлена аппаратная реализация генератора и выполнено его программное моделирование. С помощью программной модели проведено тестирование разработанного генератора псевдослучайных чисел. Использованные тесты показали положительный результат, который подтверждает высокие статистические свойства сформированной случайной последовательности
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