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Discrete Mathematics and Theoretical Computer Science Ser.: Turing's Connectionism : An Investigation of Neural Network Architectures by Christof Teuscher (2001, Trade Paperback)
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About this product
Product Identifiers
PublisherSpringer London, The Limited
ISBN-101852334754
ISBN-139781852334758
eBay Product ID (ePID)1943438
Product Key Features
Number of PagesXxiv, 200 Pages
Publication NameTuring's Connectionism : an Investigation of Neural Network Architectures
LanguageEnglish
Publication Year2001
SubjectIntelligence (Ai) & Semantics, Hardware / General, Computer Science, Neural Networks
TypeTextbook
AuthorChristof Teuscher
Subject AreaComputers
SeriesDiscrete Mathematics and Theoretical Computer Science Ser.
FormatTrade Paperback
Dimensions
Item Weight16 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
LCCN2001-042700
Dewey Edition21
Number of Volumes1 vol.
IllustratedYes
Dewey Decimal006.3/2
Table Of Content1. Introduction.- 1.1 Turing's Anticipation of Connectionism.- 1.2 Alan Mathison Turing.- 1.3 Connectionism and Artificial Neural Networks.- 1.4 Historical Context and Related Work.- 1.5 Organization of the Book.- 1.6 Book Web-Site.- 2. Intelligent Machinery.- 2.1 Machines.- 2.2 Turing's Unorganized Machines.- 2.3 Formalization and Analysis of Unorganized Machines.- 2.4 New Unorganized Machines.- 2.5 Simulation of TBI-type Machines with MATLAB.- 3. Synthesis of Logical Functions and Digital Systems with Turing Networks.- 3.1 Combinational versus Sequential Systems.- 3.2 Synthesis of Logical Functions with A-type Networks.- 3.3 Synthesis of Logical Functions with TB-type Networks.- 3.4 Multiplexer and Demultiplexer.- 3.5 Delay-Unit.- 3.6 Shift-Register.- 3.7 How to Design Complex Systems.- 3.8 Hardware Implementation.- 4. Organizing Unorganized Machines.- 4.1 Evolutionary Algorithms.- 4.2 Evolutionary Artificial Neural Networks.- 4.3 Example: Evolve Networks that Regenerate Bitstreams.- 4.4 Signal Processing in Turing Networks.- 4.5 Pattern Classification.- 4.6 Examples: Pattern Classification with Genetic Algorithms.- 4.7 A Learning Algorithm for Turing Networks.- 5. Network Properties and Characteristics.- 5.1 General Properties.- 5.2 Computational Power.- 5.3 State Machines.- 5.4 Threshold Logic.- 5.5 Dynamical Systems and the State-Space Model.- 5.6 Random Boolean Networks.- 5.7 Attractors.- 5.8 Network Stability and Activity.- 5.9 Chaos, Bifurcation, and Self-Organized Criticality.- 5.10 Topological Evolution and Self-Organization.- 5.11 Hypercomputation: Computing Beyond the Turing Limit with Turing's Neural Networks?.- 6. Epilogue.- Useful Web-Sites.- List of Figures.- List of Tables.- List of Examples, Theorems, Definitions, Propositions, and Corollaries.
SynopsisAlan Mathison Turing (1912-1954) was the first to carry out substantial re search in the field now known as Artificial Intelligence (AI). He was thinking about machine intelligence at least as early as 1941 and during the war cir culated a typewritten paper on machine intelligence among his colleagues at the Government Code and Cypher School (GC & CS), Bletchley Park. Now lost, this was undoubtedly the earliest paper in the field of AI. It probably concerned machine learning and heuristic problem-solving; both were topics that Turing discussed extensively during the war years at GC & CS, as was mechanical chess [121]. In 1945, the war in Europe over, Turing was recruited by the National Physical Laboratory (NPL)! in London, his brief to design and develop an electronic stored-program digital computer-a concrete form of the universal Turing machine of 1936 [185]. Turing's technical report "Proposed Electronic 2 Calculator" , dating from the end of 1945 and containing his design for the Automatic Computing Engine (ACE), was the first relatively complete spec ification of an electronic stored-program digital computer [193,197]. (The document "First Draft of a Report on the EDVAC", produced by John von Neumann and the Moore School group at the University of Pennsylvania in May 1945, contained little engineering detail, in particular concerning elec tronic hardware [202]., Alan Mathison Turing (1912-1954) was the first to carry out substantial re- search in the field now known as Artificial Intelligence (AI). He was thinking about machine intelligence at least as early as 1941 and during the war cir- culated a typewritten paper on machine intelligence among his colleagues at the Government Code and Cypher School (GC & CS), Bletchley Park. Now lost, this was undoubtedly the earliest paper in the field of AI. It probably concerned machine learning and heuristic problem-solving; both were topics that Turing discussed extensively during the war years at GC & CS, as was mechanical chess 121]. In 1945, the war in Europe over, Turing was recruited by the National Physical Laboratory (NPL) in London, his brief to design and develop an electronic stored-program digital computer-a concrete form of the universal Turing machine of 1936 185]. Turing's technical report "Proposed Electronic 2 Calculator", dating from the end of 1945 and containing his design for the Automatic Computing Engine (ACE), was the first relatively complete spec- ification of an electronic stored-program digital computer 193,197]. (The document "First Draft of a Report on the EDVAC", produced by John von Neumann and the Moore School group at the University of Pennsylvania in May 1945, contained little engineering detail, in particular concerning elec- tronic hardware 202]., Turing's connectionismprovides a detailed and in-depth analysis of Turing's almost forgotten ideas on connectionist machines. In a little known paper entitled "Intelligent Machinery", Turing already investigated connectionist models as early as 1948. Unfortunately, his work was dismissed by his employer as a "schoolboy essay" and went unpublished until 1968, 14 years after his death. In this book, Christof Teuscher analyzes all aspects of Turing's "unorganized machines". Turing himself also proposed a sort of genetic algorithm to train the networks. This idea has been resumed by the author and genetic algorithms are used to build and train Turing's unorganized machines. Teuscher's work starts from Turing's initial ideas, but importantly goes beyond them. Many new kinds of machines and new aspects are considered, e.g., hardware implementation, analysis of the complex dynamics of the networks, hypercomputation, and learning algorithms., Christof Teuscher revives, analyzes, and simulates Turing's ideas, applying them to different types of problems, and building and training Turing's machines using evolutionary algorithms. In a little known paper entitled 'Intelligent Machinery' Turing investigated connectionist networks, but his work was dismissed as a 'schoolboy essay'and it was left unpublished until 1968, 14 years after his death. This is not a book about today's (classical) neural networks, but about the neuron network-like structures proposed by Turing. One of its novel features is that it actually goes beyond Turing's ideas by proposing new machines. The book also contains a Foreward by B. Jack Copeland and D. Proudfoot.
LC Classification NumberQ334-342
