Artificial Intelligence and Scientific Method
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Product details:
- Publisher OUP Oxford
- Date of Publication 5 September 1996
- ISBN 9780198751588
- Binding Hardback
- No. of pages190 pages
- Size 225x144x16 mm
- Weight 346 g
- Language English
- Illustrations line figures, tables 0
Categories
Short description:
Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy. Taking a clear, non-technical approach, Donald Gillies shows how current views on scientific method are challenged by this recent research, and suggests a new framework for the study of logic. Finally, he draws on work by such seminal thinkers as Bacon, Gödel, Popper, Penrose, and Lucas, to address the hotly contested question of whether computers might become intellectually superior to human beings.
MoreLong description:
Artificial Intelligence and Scientific Method examines the remarkable advances made in the field of AI over the past twenty years, discussing their profound implications for philosophy.
Taking a clear, non-technical approach, Donald Gillies focuses on two key topics within AI: machine learning in the Turing tradition and the development of logic programming and its connection with non-monotonic logic. Demonstrating how current views on scientific method are challenged by this recent research, he goes on to suggest a new framework for the study of logic. Finally, Professor Gillies draws on work by such seminal thinkers as Bacon, Gödel, Popper, Penrose, and Lucas to address the hotly contested question of whether computers might become intellectually superior to human beings.
crisp, clear and concise
Table of Contents:
Preface
Acknowledgements
Chapter 1 The Inductivist Controversy, or Bacon versus Popper
Bacon's Inductivism
Popper's Falsificationism
Kepler's Discovery of the Laws of Planetary Motion
The Discovery of the Sulphonamide Drugs
Chapter 2 Machine Learning in the Turing Tradition
The Turing Tradition
The Practical Problem: Expert Systems and Feigenbaum's Bottleneck
Attribute-based Learning, Decision Trees, and Quinlan's ID3
GOLEM as an example of Relational Learning
Bratko's summary of the successes of Machine Learning in the Turing Tradition, 1992
GOLEM's Discovery of a Law of Nature
Chapter 3: How Advances in Machine Learning affect the Inductivist Controversy
Bacon's Example of Heat
The Importance of Falsification
Bacon's Method has only recently come to be used
The Need for Background Knowledge
Chapter 4: Logic and Programming and a New Framework for Logic
The Development of PROLOG
PROLOG as a Non-Monotonic Logic
Two Examples of Translations from One Logical System to Another
Logic = Inference + Control
PROLOG introduces Control into Deductive Logic
PROLOG and Certainty. Is Logic a priori or empirical?
Chapter 5: Can there be an Inductive Logic?
The Divergence between Deductive and Inductive Logic (up to the early 1970s)
Inductive Logic as Inference + Control
Confirmation Values as Control in a Deductive Logic
The Empirical Testing of Rival Logics
Chapter 6: Do Gödel's Incompleteness Theorems place a Limit on Artificial Intelligence?
Anxieties caused by Advances in AI
Informal Exposition of Gödel's Incompleteness Theorems
The Lucas Argument
Objections to the Lucas Argument: i) Possible Limitations on Self-Knowledge
Objections to the Lucas Argument: ii) Possible Additions of Learning Systems
Why Advances in Computing are more likely to Stimulate Human Thinking than to Render it Superfluous
Notes, References, Index
