Mind and Machine

Overview

Mind and Machine offers both an up-to-date overview of central questions and topics in the philosophy of artificial intelligence, as well as a distinct stance on many of the key debates, all the while focusing on two central questions:

- Could a machine think? and
- Are we such machines?

The book covers the philosophical and historical foundations of AI, as well as specific topics in classical, connectionist, dynamical and embodied AI, including the Turing Test, the Chinese Room...

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Overview

Mind and Machine offers both an up-to-date overview of central questions and topics in the philosophy of artificial intelligence, as well as a distinct stance on many of the key debates, all the while focusing on two central questions:

- Could a machine think? and
- Are we such machines?

The book covers the philosophical and historical foundations of AI, as well as specific topics in classical, connectionist, dynamical and embodied AI, including the Turing Test, the Chinese Room thought experiment, Gödelian arguments against AI, The Singularity, and a detailed discussion of many famous AI models. It also offers an annotated bibliography of suggested further readings, and can thus be used either as a standalone overview, or as a companion to a selection of key primary sources in AI.

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Product Details

  • ISBN-13: 9780230302945
  • Publisher: Palgrave Macmillan
  • Publication date: 10/2/2012
  • Series: Palgrave Philosophy Today Series
  • Pages: 176
  • Product dimensions: 5.40 (w) x 8.40 (h) x 0.50 (d)

Meet the Author

JOEL WALMSLEY is a Lecturer in Philosophy at University College Cork in Ireland. His research interests are in philosophy of cognitive science (especially concerning Artificial Intelligence and Dynamical Systems Theory), philosophy of science (especially concerning explanation) and philosophy of mind (especially concerning emergence and the "extended mind" hypothesis). His previous works include Mind: Historical and Philosophical Introduction to the Major Theories (Hackett: 2006. Co-authored with A. Kukla).

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Table of Contents

1. Historical and Theoretical Background

2. Classical Cognitive Science and "Good Old Fashioned" AI

3. Godel, The Turing Test and the Chinese Room

4. Connectionism and Neural Networks

5. Criticisms and Consequences of the Connectionist Approach

6. From AI to A-Life: Dynamical and Embodied Approaches

7. The Future: Cyborgs, Hybrids and Human Nature

Glossary

Annotated Bibliography and Suggestions for Further Reading

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