Principles for constructing intelligent systems
Design of Logic–based Intelligent Systems develops principles and methods for constructing intelligent systems for complex tasks that are readily done by humans but are difficult for machines. Current Artificial Intelligence (AI) approaches rely on various constructs and methods (production rules, neural nets, support vector machines, fuzzy logic, Bayesian networks, etc.). In contrast, this book uses an extension of propositional logic that treats all aspects of intelligent systems in a unified and mathematically compatible manner.
- Levels of thinking and logic
- Special cases: expert systems and intelligent agents
- Formulating and solving logic systems
- Reasoning under uncertainty
- Learning logic formulas from data
- Nonmonotonic and incomplete reasoning
- Question–and–answer processes
- Intelligent systems that construct intelligent systems
Design of Logic–based Intelligent Systems is both a handbook for the AI practitioner and a textbook for advanced undergraduate and graduate courses on intelligent systems. Included are more than forty algorithms, and numerous examples and exercises. The purchaser of the book may obtain an accompanying software package (Leibniz System) free of charge via the internet at leibnizsystem.com.
Chapter 1. Introduction.
PART I: LOGIC PROBLEMS.
Chapter 2. Introduction to Logic and Problems SAT and MINSAT.
Chapter 3. Variations of SAT and MINSAT.
Chapter 4. Quantified SAT and MINSAT.
PART II: FORMULATION OF LOGIC SYSTEMS.
Chapter 5. Basic Formulation Techniques.
Chapter 6. Uncertainty.
PART III: LEARNING.
Chapter 7. Learning Formulas.
Chapter 8. Accuracy of Learning Formulas.
PART IV: ADVANCED REASONING.
Chapter 9. Nonmonotonic and Incomplete Reasoning.
Chapter 10. Question–and–Answer Processes.
PART V: APPLICATIONS.
Chapter 11. Applications.