Turings Connectionism: An Investigation of Neural Network ArchitecturesAlan 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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Saturs
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 | 20 |
214 Practical Computing Machines | 21 |
215 Ptype Machines | 22 |
221 Fundamentals and Definitions | 23 |
222 Atype Unorganized Machines | 26 |
224 Turings Education of Machinery | 28 |
225 BItype Unorganized Machines | 29 |
23 Formalization and Analysis of Unorganized Machines | 31 |
231 Formalization of Atype Networks | 32 |
232 Formalization of Btype Links | 37 |
233 Formalization of Btype Networks | 41 |
234 Formalization of BItype Links | 42 |
235 Formalization of BItype Networks | 44 |
236 The Btype Pitfall | 45 |
24 New Unorganized Machines | 48 |
242 TBtype Unorganized Machines | 50 |
243 TBItype Unorganized Machines | 51 |
244 BStype Unorganized Machines | 52 |
245 BI1type Link | 54 |
25 Simulation of TBItype Machines with MATLAB | 55 |
3 Synthesis of Logical Functions and Digital Systems with Turing Networks | 63 |
32 Synthesis of Logical Functions with Atype Networks | 64 |
33 Synthesis of Logical Functions with TBtype Networks | 67 |
35 DelayUnit | 70 |
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 |
187 | |
197 | |
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Turings Connectionism: An Investigation of Neural Network Architectures Christof Teuscher Ierobežota priekšskatīšana - 2012 |
Bieži izmantoti vārdi un frāzes
A-type machine A-type network activity activity level algorithm allow already artificial attractors B-type link behaviour bitstream boolean networks brain built called classification clock cycles complex computing connections considered constructed contains CP-type defined Definition delay described digital system disabled dynamical systems elements enabled encoding evolution example experiments Figure finite fitness flip-flop further genetic genome given hardware human ideas implementation incoming links initial input nodes intelligence interconnection interesting interfering inputs learning length logical functions Machinery matrix means NAND gate nets network activity network nodes neural networks neurons Note operation organized output pattern perform possible presented problem proposed Proposition random randomly reader realized representation resulting rule seen shown shows signal simple simulated stable steps structure switch Table TBI-type network threshold Turing machine Turing networks Turing's Typical unit universal unorganized machine values vector weights