Chapter Outline: (or see the detailed table of contents (postscript))

• 1. Introduction
• 2. Concept Learning and the General-to-Specific Ordering
• 3. Decision Tree Learning
• 4. Artificial Neural Networks
• 5. Evaluating Hypotheses
• 6. Bayesian Learning
• 7. Computational Learning Theory
• 8. Instance-Based Learning
• 9. Genetic Algorithms
• 10. Learning Sets of Rules
• 11. Analytical Learning
• 12. Combining Inductive and Analytical Learning
• 13. Reinforcement Learning