George / Kerkut The Brain as a Computer

International Series of Monographs on Pure and Applied Biology: Zoology
1. Auflage 2013
ISBN: 978-1-4831-5023-9
Verlag: Elsevier Science & Techn.
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 488 Seiten, Web PDF

The Brain as a Computer, Second Edition is a 14-chapter book that outlines the principles of cybernetics in relation to behavior, from the perspective of experimental psychology and neurophysiology. This book begins by describing the main ideas of cybernetics. Subsequent chapters explore cybernetic models, with emphasis on finite automata, and particularly finite automata in logical net form, which seem especially useful to the modeling of behavior. Other chapters summarize learning theory, neurological matters, thinking, perception, and artificial intelligence.

Autoren/Hrsg.

George, F. H.

Kerkut, G. A.

Inhaltsverzeichnis

1;Front Cover;1
2;The Brain as a Computer;4
3;Copyright Page;5
4;Table of Contents;8
5;Dedication;6
6;Foreword to the Second Edition;10
7;CHAPTER 1.
THE ARGUMENT;14
7.1;Summary;26
8;CHAPTER 2.
CYBERNETICS;28
8.1;Mathematics;28
8.2;Historical;33
8.3;Computers;36
8.4;The general form of a digital computer;37
8.5;The language of computers;38
8.6;Systems analysis and programming;39
8.7;Digital and analog systems;40
8.8;Neurophysiology and psychology;41
8.9;Communication theory;43
8.10;The technical aspect of communication;47
8.11;Language, syntax, semantics and pragmatics;50
8.12;Servosystems;51
8.13;Finite automata;53
8.14;Summary;54
9;CHAPTER 3.
PHILOSOPHY, METHODOLOGY AND
CYBERNETICS;56
9.1;Cybernetics and philosophy;60
9.2;Viewpoints in philosophy;61
9.3;Convenient classifications;62
9.4;Language;62
9.5;Scientific theory construction;63
9.6;The nature of science in general;64
9.7;Psychological theory;65
9.8;Models;68
9.9;Logic and cybernetics;69
9.10;Logic in ordinary language;69
9.11;Paper and pencil machines;80
9.12;Turing machines;82
9.13;Machines and biology;87
9.14;The evolution of scientific theories;88
9.15;Explanation;93
9.16;Empirical logics;96
9.17;Stochastic processes;100
9.18;The end of the anecdote;101
9.19;Summary;101
10;CHAPTER 4.
FINITE AUTOMATA;104
10.1;Automata theory;104
10.2;McCulloch-Pitts neural net;108
10.3;Uneconomical finite automata;112
10.4;The multiple-line trick;116
10.5;The syntheses of finite automata;120
10.6;Grey Walter's models;120
10.7;Technical description of M. speculatrix;121
10.8;Ross Ashby's model;123
10.9;Shannon's model;125
10.10;Uttley's models;127
10.11;Chapman's self-organizing classification system;129
10.12;General synthesis;131
10.13;Summary;132
11;CHAPTER 5.
LOGICAL NETS;134
11.1;Classification systems;145
11.2;Theory of perception;153
11.3;Motivation;155
11.4;Emotion;157
11.5;Memory;158
11.6;Flebus;159
11.7;George's models;162
11.8;General;162
11.9;Some points from controversy in cognition;164
11.10;Probabilistic considerations within the deterministic network;167
11.11;Multiplexing;168
11.12;Hierarchical nets;169
11.13;Summary;170
12;CHAPTER 6.
THEORY OF GAMES;172
12.1;Games against nature;174
12.2;Dynamic programming;175
12.3;Empirical games;176
13;CHAPTER 7.
PROGRAMMING COMPUTERS TO SOLVE
PROBLEMS;178
13.1;Programming the computer to play a simple game;180
13.2;Generalizations on game playing;187
13.3;General inductive programming;190
13.4;Heuristic programming;193
13.5;Heuristic generation;194
13.6;Language for the computer;196
13.7;Changing goals;197
13.8;Cybernetics and learning;198
13.9;Summary;202
14;CHAPTER 8.
PSYCHOLOGICAL THEORY OF
LEARNING;204
14.1;Hull's theory of learning;220
14.2;Tolman's theory;225
14.3;Partial reinforcement, latent learning and some other variables;232
14.4;Latent learning;239
14.5;Other problems of learning;242
14.6;Matrix representation of logical nets;243
14.7;Retroactive inhibition;244
14.8;Transfer of training;246
14.9;Stimulus generalization;246
14.10;Learning sets;249
14.11;Extinction;254
14.12;Recent advances;257
14.13;Summary;261
15;CHAPTER 9.
BEHAVIOUR AND THE NERVOUS
SYSTEM;262
15.1;Chemistry of the nervous system;272
15.2;The nervous system;277
15.3;Information theory and nervous impulses;283
15.4;Methodology;287
15.5;Electrical techniques;288
15.6;Sensory deprivation;291
15.7;The myelencephalon;292
15.8;The metencephalon;292
15.9;The mesencephalon;293
15.10;The reticular system;293
15.11;The diencephalon;296
15.12;Thalamus and hypothalamus;296
15.13;The telencephalon;298
15.14;The cerebral cortex;299
15.15;Cortical stimulation;306
15.16;Temporal and parietal areas and motor-sensory cortical areas;307
15.17;Aphasia;313
15.18;Evidence on conditioned reflexes;314
15.19;Further experimental evidence;316
15.20;Summary;318
16;CHAPTER 10.
THEORIES AND MODELS OF
THE NERVOUS SYSTEM;320
16.1;Konorski's model;325
16.2;The ethologists;329
16.3;Lashley's theory;330
16.4;Early and late brain injuries;331
16.5;Beurle's model;334
16.6;Ashby's model;334
16.7;Hebb's cell assembly and Milner's Mark II cell assembly;335
16.8;Pribram's brain model;339
16.9;Cybernetic models in general;343
16.10;Automata theory and brain models;344
16.11;Neural nets as automata;346
16.12;General hardware and software models;348
16.13;Summary;349
17;CHAPTER 11.
PERCEPTION;352
17.1;Cybernetics and perception;357
17.2;The machine design;359
17.3;Empirical classification in terms of classes or properties;362
17.4;The counting system;363
17.5;The temporal order;364
17.6;The effective stimulus in perception;368
17.7;Psycho-physic;370
17.8;Form perception;371
17.9;Selfridge's visual pattern recognition model;375
17.10;Deutsch's visual model;377
17.11;Hebb's model for perception;377
17.12;Perceptrons;379
17.13;Culbertson's model;382
17.14;Banerji's model;384
17.15;A model for perception;386
17.16;Summary;398
18;CHAPTER 12.
PATTERN RECOGNITION;400
18.1;Perceptual models;402
18.2;Movement after-effects;406
18.3;Other perceptual models;409
18.4;Pattern recognition and central cognition;409
18.5;Summary;415
19;CHAPTER 13.
ARTIFICIAL INTELLIGENCE;418
19.1;Concepts;419
19.2;Structure;421
19.3;Hypotheses;421
19.4;Language;422
19.5;Logic;426
19.6;Pattern recognition;427
19.7;Representation of problems;428
19.8;Data collection;429
19.9;Evidence;430
19.10;Concluding remarks;432
20;CHAPTER 14.
SUMMARY;434
20.1;A brain model in outline;447
21;APPENDIX:
SOME RECENT BRAIN MODELS;454
22;REFERENCES;458
23;AUTHOR INDEX;480
24;SUBJECT INDEX;486