Turing’s Connectionism: An Investigation of Neural Network Architectures

Pirmais vāks
Springer Science & Business Media, 2002 - 200 lappuses
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].

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1 Introduction
1
12 Alan Mathison Turing
4
13 Connectionism and Artificial Neural Networks
6
14 Historical Context and Related Work
10
15 Organization of the Book
13
16 Book WebSite
15
2 Intelligent Machinery
17
21 Machines
18
38 Hardware Implementation
77
4 Organizing Unorganized Machines
83
41 Evolutionary Algorithms
84
42 Evolutionary Artificial Neural Networks
86
422 Encoding Techniques
87
423 Atype Network Encoding
88
424 Btype Network Encoding
90
426 LSystem Encoding
93

212 Turing Machines
19
213 Universal Turing Machines
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214 Practical Computing Machines
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215 Ptype Machines
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221 Fundamentals and Definitions
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222 Atype Unorganized Machines
26
224 Turings Education of Machinery
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225 BItype Unorganized Machines
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23 Formalization and Analysis of Unorganized Machines
31
231 Formalization of Atype Networks
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232 Formalization of Btype Links
37
233 Formalization of Btype Networks
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234 Formalization of BItype Links
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235 Formalization of BItype Networks
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236 The Btype Pitfall
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24 New Unorganized Machines
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242 TBtype Unorganized Machines
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243 TBItype Unorganized Machines
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244 BStype Unorganized Machines
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245 BI1type Link
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25 Simulation of TBItype Machines with MATLAB
55
3 Synthesis of Logical Functions and Digital Systems with Turing Networks
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32 Synthesis of Logical Functions with Atype Networks
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33 Synthesis of Logical Functions with TBtype Networks
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35 DelayUnit
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36 ShiftRegister
72
37 How to Design Complex Systems
74
Evolve Networks that Regenerate Bitstreams
97
44 Signal Processing in Turing Networks
101
45 Pattern Classification
106
Pattern Classification with Genetic Algorithms
109
47 A Learning Algorithm for Turing Networks
117
5 Network Properties and Characteristics
121
52 Computational Power
123
53 State Machines
125
54 Threshold Logic
127
55 Dynamical Systems and the StateSpace Model
131
56 Random Boolean Networks
133
57 Attractors
135
58 Network Stability and Activity
138
581 Activity in Atype Networks
142
582 Activity in BStype Networks
144
583 Activities in TBtype and TBItype Networks
147
59 Chaos Bifurcation and SelfOrganized Criticality
148
510 Topological Evolution and SelfOrganization
157
Computing Beyond the Turing Limit with Turings Neural Networks?
163
6 Epilogue
169
Useful WebSites
171
List of Figures
173
List of Tables
181
List of Examples Theorems Definitions Propositions and Corollaries
183
Bibliography
187
Index
197
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