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E-raamat: Turing's Connectionism: An Investigation of Neural Network Architectures

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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Machinery' Turing investigated connectionist networks, but his work was dismissed as a 'schoolboy essay'and it was left unpublished until 1968, 14 years after his death.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.

Turing's connectionism provides 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 Unfortunately, his work was dismissed by his employer as a "schoolboy essay" and went unpublished until 1968, 14 years after his death.In this book, Christof Teuscher analyzes all aspects of Turing's "unorganized machines".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.

Muu info

Springer Book Archives
Introduction
1(16)
Turing's Anticipation of Connectionism
1(3)
Alan Mathison Turing
4(2)
Connectionism and Artificial Neural Networks
6(4)
Historical Context and Related Work
10(3)
Organization of the Book
13(2)
Book Web--Site
15(2)
Intelligent Machinery
17(46)
Machines
18(4)
Technical Terms
18(1)
Turing Machines
19(1)
Universal Turing Machines
20(1)
Practical Computing Machines
21(1)
P-type Machines
22(1)
Turing's Unorganized Machines
22(9)
Fundamentals and Definitions
23(3)
A-type Unorganized Machines
26(1)
B-type Unorganized Machines
26(2)
Turing's ``Education'' of Machinery
28(1)
Bl-type Unorganized Machines
29(2)
Formalization and Analysis of Unorganized Machines
31(17)
Formalization of A-type Networks
32(5)
Formalization of B-type Links
37(4)
Formalization of B-type Networks
41(1)
Formalization of Bl-type Links
42(2)
Formalization of Bl-type Networks
44(1)
The B-type Pitfall
45(3)
New Unorganized Machines
48(7)
CP-type Unorganized Machines
48(2)
TB-type Unorganized Machines
50(1)
TBI-type Unorganized Machines
51(1)
BS-type Unorganized Machines
52(2)
Bl1-type Link
54(1)
Simulation of TBI-type Machines with MATLAB
55(8)
MATLAB
55(1)
A Simple TBI-type MATLAB Toolbox
55(8)
Synthesis of Logical Functions and Digital Systems with Turing Networks
63(20)
Combinational versus Sequential Systems
63(1)
Synthesis of Logical Functions with A-type Networks
64(3)
Synthesis of Logical Functions with TB-type Networks
67(1)
Multiplexer and Demultiplexer
67(3)
Delay-Unit
70(2)
Shift-Register
72(2)
How to Design Complex Systems
74(3)
Hardware Implementation
77(6)
Organizing Unorganized Machines
83(38)
Evolutionary Algorithms
84(2)
Evolutionary Artificial Neural Networks
86(11)
Fundamentals
86(1)
Encoding Techniques
87(1)
A-type Network Encoding
88(2)
B-type Network Encoding
90(1)
Architecture versus Configuration
90(3)
L-System Encoding
93(4)
Example: Evolve Networks that Regenerate Bitstreams
97(4)
Signal Processing in Turing Networks
101(5)
Pattern Classification
106(3)
Examples: Pattern Classification with Genetic Algorithms
109(8)
A Learning Algorithm for Turing Networks
117(4)
Network Properties and Characteristics
121(48)
General Properties
121(2)
Computational Power
123(2)
State Machines
125(2)
Threshold Logic
127(4)
Dynamical Systems and the State-Space Model
131(2)
Random Boolean Networks
133(2)
Attractors
135(3)
Network Stability and Activity
138(10)
Activity in A-type Networks
142(2)
Activity in BS-type Networks
144(3)
Activities in TB-type and TBl-type Networks
147(1)
Chaos, Bifurcation, and Self-Organized Criticality
148(9)
Topological Evolution and Self-Organization
157(6)
Hypercomputation: Computing Beyond the Turing Limit with Turing's Neural Networks?
163(6)
Epilogue
169(2)
Useful Web-Sites 171(2)
List of Figures 173(8)
List of Tables 181(2)
List of Examples, Theorems, Definitions, Propositions, and Corollaries 183(4)
Bibliography 187(10)
Index 197