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Mar 1997
ISBN 0262082594
488 pp.
Mind Design II
John Haugeland

"Mind Design II is a welcome update of its predecessor, itself a useful compendium on the philosophy of cognitive science. This new volume retains the intellectual foundations, and some discussions of classical AI built on them, while adding connectionism, situated AI, and dynamic systems theory as extra storeys. Which of these is the most stable, and whether the foundations need to be re-worked, are questions readers will be eager to explore."
-- Margaret A. Boden, Professor of Philosophy and Psychology, University of Sussex, UK

"Haugeland's Mind Design II brings together nearly all the essential philosophical perspectives in Cognitive Science. If you want to understand current opinion on the philosophy of mind, you should make sure you are familiar with the contents of this book."
-- James L. McClelland, Carnegie Mellon University and the Center for the Neural Basis of Cognition

Mind design is the endeavor to understand mind (thinking, intellect) in terms of its design (how it is built, how it works). Unlike traditional empirical psychology, it is more oriented toward the "how" than the "what." An experiment in mind design is more likely to be an attempt to build something and make it work--as in artificial intelligence--than to observe or analyze what already exists. Mind design is psychology by reverse engineering.

When Mind Design was first published in 1981, it became a classic in the then-nascent fields of cognitive science and AI. This second edition retains four landmark essays from the first, adding to them one earlier milestone (Turing's "Computing Machinery and Intelligence") and eleven more recent articles about connectionism, dynamical systems, and symbolic versus nonsymbolic models. The contributors are divided about evenly between philosophers and scientists. Yet all are "philosophical" in that they address fundamental issues and concepts; and all are "scientific" in that they are technically sophisticated and concerned with concrete empirical research.

Table of Contents
1 What Is Mind Design?
by John Haugeland
2 Computing Machinery and Intelligence
by A. M. Turing
3 True Believers: The Intentional Strategy and Why It Works
by Daniel C. Dennett
4 Computer Science as Empirical Inquiry: Symbols and Search
by Allen Newell and Herbert A. Simon
5 A Framework for Representing Knowledge
by Marvin Minsky
6 From Micro-Worlds to Knowledge Representation: AI at an Impasse
by Hubert L. Dreyfus
7 Minds, Brains, and Programs
by John R. Searle
8 The Architecture of Mind: A Connectionist Approach
by David E. Rumelhart
9 Connectionist Modeling: Neural Computation / Mental Connections
by Paul Smolensky
10 On the Nature of Theories: A Neurocomputational Perspective
by Paul M. Churchland
11 Connectionism and Cognition
by Jay F. Rosenberg
12 Connectionism and Cognitive Architecture: A Critical Analysis
by Jerry A. Fodor and Zenon W. Pylyshyn
13 Connectionism, Eliminativism, and the Future of Folk Psychology
by William Ramsey, Stephen Stich and Joseph Garon
14 The Presence of a Symbol
by Andy Clark
15 Intelligence without Representation
by Rodney A. Brooks
16 Dynamics and Cognition
by Timothy van Gelder
Related Topics
Computational Intelligence

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