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Unorganized Machines: From Turing’s Ideas to Modern Connectionist Approaches
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Author(s): Levy Boccato (University of Campinas (UNICAMP), Brazil), Everton S. Soares (University of Campinas (UNICAMP), Brazil), Marcos M. L. P. Fernandes (Faculdade de Engenharia de Sorocaba (FACENS), Brazil), Diogo C. Soriano (Federal University of ABC (UFABC), Brazil)and Romis Attux (University of Campinas (UNICAMP), Brazil)
Copyright: 2014
Pages: 16
Source title:
Natural Computing for Simulation and Knowledge Discovery
Source Author(s)/Editor(s): Leandro Nunes de Castro (Mackenzie University, Brazil)
DOI: 10.4018/978-1-4666-4253-9.ch015
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Abstract
This work presents a discussion about the relationship between the contributions of Alan Turing – the centenary of whose birth is celebrated in 2012 – to the field of artificial neural networks and modern unorganized machines: reservoir computing (RC) approaches and extreme learning machines (ELMs). Firstly, the authors review Turing’s connectionist proposals and also expose the fundamentals of the main RC paradigms – echo state networks and liquid state machines, - as well as of the design and training of ELMs. Throughout this exposition, the main points of contact between Turing’s ideas and these modern perspectives are outlined, being, then, duly summarized in the second and final part of the work. This paper is useful in offering a distinct appreciation of Turing’s pioneering contributions to the field of neural networks and also in indicating some perspectives for the future development of the field that may arise from the synergy between these views.
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