Description: PrefaceAcknowledgementsChapter 1: The Inductivist Controversy, or Bacon versus Popper1.1. Bacon's Inductivism1.2. Popper's Falsificationism1.3. Kepler's Discovery of the Laws of Planetary Motion1.4. The Discovery of the Sulphonamide DrugsChapter 2: Machine Learning in the Turing Tradition2.1. The Turing Tradition2.2. The Practical Problem: Expert Systems and Feigenbaum's Bottleneck2.3. Attribute-based Learning, Decision Trees, and Quinlan's ID32.4. GOLEM as an example of Relational Learning2.5. Bratko's summary of the successes of Machine Learning in the Turing Tradition, 19922.6. GOLEM's Discovery of a Law of NatureChapter 3: How Advances in Machine Learning affect the Inductivist Controversy3.1. Bacon's Example of Heat3.2. The Importance of Falsification3.3. Bacon's Method has only recently come to be used3.4. The Need for Background KnowledgeChapter 4: Logic and Programming and a New Framework for Logic4.1. The Development of PROLOG4.2. PROLOG as a Non-Monotonic Logic4.3. Two Examples of Translations from One Logical System to Another4.4. Logic = Inference + Control4.5. PROLOG introduces Control into Deductive Logic4.6. PROLOG and Certainty. Is Logic a priori or empirical?Chapter 5: Can there be an Inductive Logic?5.1. The Divergence between Deductive and Inductive Logic (up to the early 1970s)5.2. Inductive Logic as Inference + Control5.3. Confirmation Values as Control in a Deductive Logic5.4. The Empirical Testing of Rival LogicsChapter 6: Do Gdel's Incompleteness Theorems place a Limit on Artificial Intelligence?6.1. Anxieties caused by Advances in AI6.2. Informal Exposition of Gdel's Incompleteness Theorems6.3. The Lucas Argument6.4. Objections to the Lucas Argument: i) Possible Limitations on Self-Knowledge6.5. Objections to the Lucas Argument: ii) Possible Additions of Learning Systems6.6. Why Advances in Computing are more likely to Stimulate Human Thinking than to Render it SuperfluousNotes References Index

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