Rethinking Cognitive Computation Turing and the Science of the Mind

by Wells, Andy

• ISBN13: 9781403911612
• ISBN10: 1403911614
• Format: Hardcover
• Copyright: 2005-12-17
• Publisher: Red Globe Pr

Summary

This book provides a detailed understanding of the computational foundations of cognitive science. The author makes a critical evaluation of the symbol processing and connectionist approaches which constitute the current mainstream; and offers a new computational framework for cognitive science.

Author Biography

Andy Wells is Lecturer in Psychology at the London School of Economics.

Table of Contents

List of Figures	xiii
List of Tables	xv
Acknowledgement	xvii
Preface	xviii
1. Introduction	1	(10)
Computable numbers	1	(1)
Turing's later work	2	(1)
Computation in cognitive science	3	(1)
The reception and understanding of Turing's work	4	(3)
Summary and goals of the book	7	(4)
2. Making the Modern Mind	11	(11)
Introduction	11	(1)
William James: mind, brain and consciousness	12	(1)
J.B. Watson: behaviourism	13	(1)
F.C. Bartlett: the effort after meaning	14	(2)
Kenneth Craik: mental models	16	(1)
McCulloch and Pitts: artificial neural networks	17	(1)
John von Neumann: computer architecture	17	(1)
Donald Hebb: the neuropsychology of learning	18	(1)
Miller, Galanter and Pribram: plans	18	(1)
Newell and Simon: physical symbol systems	19	(1)
llumelhart and McClelland: PDP	20	(1)
The current situation	20	(2)
3. Functional States and Mini-minds	22	(11)
Introduction	22	(1)
Functional states and processes	22	(1)
Computing numbers	23	(1)
Functional states and everyday processes	24	(1)
Functional and physical analysis	25	(2)
Representing happiness and sadness	27	(3)
Mini-minds	30	(3)
4. Exploring Sets of Mini-minds	33	(20)
Configurations	33	(1)
Instructions and machine tables	33	(1)
Deterministic and non-deterministic models	34	(1)
Description numbers	35	(1)
Logical possibility and psychological plausibility	36	(1)
Counting mini-minds	36	(1)
Four-state mini-minds	37	(1)
Plausibility constraints: selecting subsets of mini-minds	38	(8)
Appendix 4.1 Binary to decimal and decimal to binary conversion	46	(1)
Appendix 4.2 Thirty-six four-state, two-input mini-minds	47	(6)
5. Environments and Actions	53	(21)
Introduction	53	(1)
Specifying places	53	(1)
Places and objects	54	(2)
Linear environments	56	(1)
Situated mini-minds	57	(1)
Getting inside a mini-mind	57	(1)
The first sheep and dogs Turing machine	58	(2)
Complete configurations and traces of behaviour	60	(2)
Configuration-governed and rule-governed behaviour	62	(1)
A further example	63	(3)
Memory in mini-minds	66	(2)
Counting situated mini-minds	68	(1)
Summary	69	(1)
Appendix 5.1 Answers to sheep and dog exercises	70	(4)
6. Turing's Analysis of Computation	74	(14)
Introduction	74	(1)
Terminology	75	(1)
The scope of Turing's analysis	75	(3)
Derivation of the machine model	78	(8)
The construction of a machine to do the work of a computant	86	(2)
7. Turing's Example Machines	88	(10)
m-configurations, configurations and complete configurations	88	(1)
Infinite tapes	89	(1)
Symbols of the first and second kinds	89	(1)
Circle-free and circular machines	90	(1)
Organization of the tape: F-squares and E-squares	90	(1)
Turing's first machine: TM1	91	(2)
Turing's second machine: TM2	93	(5)
8. Turing's Functional Notation	98	(8)
Skeleton tables and m-functions	98	(3)
Building composite m-functions by linking	101	(1)
Defining m-functions in terms of other m-functions	102	(4)
9. Standard Descriptions and Description Numbers	106	(7)
Introduction	106	(1)
How many Turing machines are there?	107	(1)
Standard descriptions	108	(3)
Description numbers	111	(2)
10. Basic Components of the Universal Machine	113	(10)
Introduction	113	(1)
The rightmost symbol finder	114	(1)
Printing figures	115	(1)
Copying marked symbols	116	(1)
Copying marked symbols and erasing the markers	117	(1)
Comparing marked symbols	118	(2)
Comparing marked symbols and erasing the markers	120	(2)
Marking configurations	122	(1)
11. Simulation	123	(10)
Introduction	123	(1)
The simulation cycle in outline	123	(1)
Observation and participation	124	(9)
12. The Universal Machine in Detail	133	(15)
Initiating a computation	133	(1)
Marking and matching configurations	134	(3)
Marking the tape in preparation for writing the next complete configuration	137	(4)
Printing figures	141	(3)
Printing the next complete configuration	144	(2)
Housekeeping	146	(1)
Further processing cycles	147	(1)
13. Turing's Unsolvability Proofs	148	(13)
Turing's thesis	148	(1)
Uncomputable numbers	149	(1)
The unsolvability of the halting problem	150	(4)
The unsolvability of the printing problem	154	(1)
The unsolvability of the Entscheidungsproblem	155	(1)
Unsolvability proofs and the nature of the mind	156	(3)
Gödel and Turing	159	(2)
14. Von Neumann Computer Architecture	161	(13)
Introduction	161	(1)
Turing's instruction note mode!	162	(2)
The ENIAC	164	(1)
John von Neumann and the stored program concept	165	(1)
The design of the EDVAC	166	(1)
The case for serial processing	167	(2)
Internal organization of von Neumann architecture	169	(5)
15. Virtual Architecture	174	(9)
Standard descriptions as virtual machines	174	(1)
Hierarchies of virtual machines	175	(1)
The mind as virtual machine	176	(1)
Virtual machines depend on the underlying hardware	177	(1)
Virtual control regimes	178	(1)
Production systems	179	(1)
Turing machines and production systems	180	(2)
Summary	182	(1)
16. The Commitments of the Computational Theory of Mind	183	(15)
Introduction	183	(2)
The CTM and von Neumann architecture	185	(2)
Fudging the issues	187	(3)
Can you make a computer out of anything?	190	(1)
Is everything a computer?	191	(3)
The attractions of the computational theory of mind	194	(4)
17. Evaluating the Computational Theory of Mind	198	(11)
Introduction	198	(1)
Does the brain contain flip-flops?	199	(1)
Positional specification of meaning in the brain	200	(1)
Hierarchical encoding	201	(1)
Constituency and neural constraints	202	(1)
Encoding and decoding: the transduction problem	203	(2)
Could the brain have evolved as a universal computer?	205	(3)
Summary	208	(1)
18. Connectionism	209	(15)
Introduction	209	(1)
McCulloch—Pitts networks	209	(1)
Learning in single-layer networks	210	(1)
Multi-layer networks	210	(1)
Symbol systems versus connectionism	210	(1)
Styles of connectionist modelling	211	(1)
Networks and finite automata	212	(1)
Supervised learning	212	(7)
Performance and limitations of trained feed-forward networks	219	(2)
Networks with recurrent structure	221	(1)
Problems and a proposed solution	222	(2)
19. Ecological Functionalism: Computation	224	(12)
Introduction	224	(1)
Neural and environmental structure	224	(1)
The need for a more expressive formal system	225	(1)
Studying concurrency: the π-calculus	226	(8)
Turing machines and π-calculus processes	234	(2)
20. Ecological Functionalism: Psychology	236	(16)
Introduction	236	(1)
Behavioural flexibility	237	(1)
Rational, adaptive, goal-oriented behaviour	238	(1)
Real time operation	238	(1)
Environmental embedding	239	(2)
Use of symbols and abstractions	241	(3)
Use of language, both natural and artificial	244	(1)
Learning from the environment and from experience	244	(1)
Acquisition of capabilities through development	245	(1)
Autonomous operation within a social community	245	(1)
Self-awareness and sense of self	246	(1)
Neural realization	246	(1)
Construction by an embryological growth process	247	(1)
Evolutionary history	247	(3)
Conclusion	250	(2)
References	252	(8)
Index	260