Preface

 

Darryl N. Davis

 

Neural, Emergent and Agent Technologies Research Group,

Department of Computer Science,

University of Hull,
Kingston-upon-Hull, HU6 7RX, England.


http://www2.dcs.hull.ac.uk/NEAT/index.html


E-mail: D.N.Davis AT hull.ac.uk

 

Fax: +44 (0) 1482 466666 

Tel: +44 (0) 1482 466469

 

An Introduction

This text is concerned with the study of questions such as:

·         What is mind?

·         What are theories of mind?

·         What are computationally plausible theories of mind?

·         What are computationally plausible designs based on these theories of mind?

·         What are computationally plausible architectures and systems to support theories of mind?

·         What are computationally implemented architectures and systems based on theories of mind?

·         What kind of tools can we use in producing and implementing such designs?

·         How do we know when we are successful in producing artificial minds?

Such questions have been addressed throughout the history of western civilization, from the philosophers of ancient Greece (see [Popkin & Stroll, 1993; Bechtel, 1988] for an overview), through the Age of Enlightenment, for example Descartes [Bechtel, 1988], the industrial revolution and Babbage’s designs for the Difference Engine [Swage, 2001], to the advent of the computer [Turing, 1950; von Neumann 1963] and since its inception as an academic field in its own right in Artificial Intelligence. 

Just over twenty years ago Donald Norman [1980] set an agenda of important issues for Cognitive Science: Belief Systems, Consciousness, Development, Emotion, Interaction, Language, Learning, Memory, Perception, Performance, Skill and Thought. This non-exhaustive list of topics has played an important role in determining where researchers have focussed their work.

Such study is arguably the core of the field of Artificial Intelligence [Barr & Feigenbaum, 1981; Winston, 1984; Sharples et al. 1989; Franklin, 1995; Nilsson, 1998; Russell & Norvig, 2003] and Cognitive Science [Winograd & Flores, 1986; Bechtel, 1988; Wilson & Keil, 1999].

Figure1. One Architecture (Based on Norman 1980)

An important aspect of the agenda set by Norman is the use of an architectural perspective.

One such example architecture is given in figure 1. Five interacting processes are identified: the reception of incoming signals (perception), the generation of output (action selection), a reactive or regulatory system, a deliberative or cognitive system and an emotional or affect system. Norman suggests that this is the type of architecture needed to address the twelve topics included in his agenda for cognitive science.

This topic is important both to artificial intelligence and cognitive science, and also to the academic disciplines that they draw on and feed, for instance philosophy, computer science and psychology. This text brings together a number of perspectives on these issues with contributions from leading figures in the area. It follows in the tradition of Computers and Thought (1963), Mind Design (1981), Architectures for Intelligence (1988) and Android Epistemology (1989).

References:

1.    Barr, A & Feigenbaum, E.A., The Handbook of Artificial Intelligence Volume One, Kaufmann, 1981.

2.    Bechtel, W., Philosophy of Mind: An Overview of Cognitive Science, LEA Press, 1988.

3.    Feigenbaum, E.A. & J. Feldman (Eds.), Computers and Thought, McGraw-Hill, ISBN 0-262-56092-5, 1963.

4.    Ford, K.M., C. Glymour & P. J. Hayes (Eds.), Android Epistemology, MIT Press, ISBN 0-262-06184-8, 1989.

5.    Franklin,, S.P. Artificial Minds, The MIT Press, Cambridge, Mass., 1995.

6.    Haugeland, J. (Ed.), Mind Design, MIT Press, ISBN 0-262-08110-5, 1981.

7.    Newell, A., Unified Theories of Cognition, Harvard University Press, 1990.

8.    Nilsson, N.J., Artificial Intelligence: a new synthesis, Morgan Kaufmann Publishers, 1998.

9.    Norman, D.A., Twelve issues for cognitive science, Cognitive Science, 4:1-33, 1980.

10. Popkin R.H. & A. Stroll, Philosophy (3/e), Reed Elsevier plc, ISBN: 0750609427, 1993

11. Russell, S. & Norvig, P. Artificial Intelligence : A Modern Approach (2/e), Prentice-Hall, 2003.

12. Sharples,M., D. Hogg, C. Hutchinson, S. Torrance & D. Young, Computers and Thought,  MIT Press, 1980.

13.  Swage, D., The Cogwheel Brain: Charles Babbage and the Quest to Build the First Computer., Abacus Press, ISBN: 0349112398, 2001.

14. Turing, A. Computing Machinery and Intelligence, Mind 59:433-460, October 1950.(Reprinted in)

15. VanLehn, K. (Ed.), Architectures for Intelligence, LEA Press, ISBN 0-8058-0405-6, 1988.

16. von Newmann J., General and Logical Theory of Automata, In: A.H. Taub (ed), J. von Newmann, Collected Works, Pegamon, 1963.

17. Wilson, R.A & Keil, F.C. (Editors), The MIT Encyclopedia of the Cognitive Sciences, MIT Press, 1999.

18. Winograd, T. & Flores, F., Understanding Computers and Cognition, Addison-Wesley, 1986.

19. Winston, P.H. Artificial Intelligence (2/e), Addison Wesley, 1984.