Thesis. 1976. M.S.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / Microfiche copy available in Archives and Engineering. / Includes bibliographies. / by William J. Masek. / M.S.

The Turing mechanism for the production of a broken spatial symmetry in an initially homogeneous system of reacting and diffusing substances has attracted much interest as a potential model for certain aspects of morphogenesis such as pre-patterning in the embryo, and has also served as a model for self-organization in more generic systems. The two features necessary for the formation of Turing patterns are short-range autocatalysis and long-range inhibition which usually only occur when the diffusion rate of the inhibitor is significantly greater than that of the activator. This observation has sometimes been used to cast doubt on applicability of the Turing mechanism to cellular patterning since many messenger molecules that diffuse between cells do so at more-or-less similar rates. Here we show that stationary, symmetry-breaking Turing patterns can form in physiologically realistic systems even when the extracellular diffusion coefficients are equal; the kinetic properties of the 'receiver' and 'transmitter' proteins responsible for signal transduction will be primary factors governing this process.

Thèse doctorat : Informatique : Rennes 1 : 2005. / Bibliogr. p. [129]-132.

Thèse doctorat : Informatique : Rennes 1 : 2005. / Bibliogr. p. 193-202.

The purpose of this thesis is to develop a software system simulating Turing machines using a Microsoft Windows' Interface.Developed in the 1930's by Alan Turing and Emil Post, Turing machines are defined as "abstract computers" . These machines seem able to solve all problems a modern computer can solve, however complex the problems may be. A Turing machine is a basic computational model for algorithms.The software provides a practical tool to students with a relative notion of Turing machines. The software contains introduction and general information on Turing machines that gives the beginner enough background to use the program. The user can create, modify or run Turing machines saved onto MS-DOS files. Some examples of Turing machines are preloaded. These examples give more help to the beginner.An on-line help facility is provided in order to direct and inform the learning student at each level of the software.The Microsoft Windows' Interface makes the software easy and friendly to use. The software has the modularity which will ease any future enhancement. / Department of Computer Science

Thesis (Ph. D. in Mathematics)--Vanderbilt University, Dec. 2004. / Title from title screen. Includes bibliographical references.

No description available.

abstract: There have been multiple attempts of coupling neural networks with external memory components for sequence learning problems. Such architectures have demonstrated success in algorithmic, sequence transduction, question-answering and reinforcement learning tasks. Most notable of these attempts is the Neural Turing Machine (NTM), which is an implementation of the Turing Machine with a neural network controller that interacts with a continuous memory. Although the architecture is Turing complete and hence, universally computational, it has seen limited success with complex real-world tasks. In this thesis, I introduce an extension of the Neural Turing Machine, the Neural Harvard Machine, that implements a fully differentiable Harvard Machine framework with a feed-forward neural network controller. Unlike the NTM, it has two different memories - a read-only program memory and a read-write data memory. A sufficiently complex task is divided into smaller, simpler sub-tasks and the program memory stores parameters of pre-trained networks trained on these sub-tasks. The controller reads inputs from an input-tape, uses the data memory to store valuable signals and writes correct symbols to an output tape. The output symbols are a function of the outputs of each sub-network and the state of the data memory. Hence, the controller learns to load the weights of the appropriate program network to generate output symbols. A wide range of experiments demonstrate that the Harvard Machine framework learns faster and performs better than the NTM and RNNs like LSTM, as the complexity of tasks increases. / Dissertation/Thesis / Masters Thesis Computer Science 2020

Traditional recursion theory is the study of computable functions on the natural numbers. This thesis considers recursion theory in first-order arithmetical theories and categories, thus expanding the work of Ritchie and Young, Lambek, Scott, and Hofstra. We give a complete characterisation of the representability of computable functions in arithmetical theories, paying attention to the differences between intuitionistic and classical theories and between theories with and without induction. When considering recursion theory from a category-theoretic perspective, we examine syntactic categories of arithmetical theories. In this setting, we construct a strong parameterised natural numbers object and give necessary and sufficient conditions to construct a Turing category associated to an intuitionistic arithmetical theory with induction.

Face à la révolution numérique qui parcourt l’aube de ce nouveau siècle, des mutations s’engagent, soulevant de nouvelles questions pour l’humanité. Les postulats humanistes et les propositions des Lumières vont venir éclairer le questionnement autour de l’augmentation de l’Homme porté par le transhumanisme.Nous allons explorer en quoi ces thèses ont enclenché depuis plusieurs siècles une réification de l’Homme et de son monde. La révolution technique entreprise par Turing et celle philosophique, portée par la cybernétique, vont venir proposer une vision algorithmique de l’Homme et de sa réalité. Ce que nous avons appelé le Monde de Turing en est l’aboutissement, faisant de l’homme informationnel, le cybernanthrope, son esclave. Face au totalitarisme libéral de la techné, nous avons identifié un postulat éthique porté par ce que nous avons appelé le delta de Turing. Dès lors, il est possible et nécessaire de faire une critique de la raison artificielle donnant naissance à une éthique pratique de la vertu partagée. Ensuite, nous pourrons analyser comment l’intelligence artificielle peut nous aider à créer une éthique pragmatique des valeurs partagées entre Homme et Machine. / Doctorat en Philosophie / info:eu-repo/semantics/nonPublished