The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods.
The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding.
Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.
1. Introduction to Artificial Intelligence Part 1: Logical Intelligence 2. Propositional Logic 3. First-Order Logic 4. Certain Knowledge Representation 5. Learning Deterministic Models Part 2: Probabilistic Intelligence 6. Probability 7. Uncertain Knowledge Representation 8. Advanced Properties of Bayesian Network 9. Decision Analysis 10. Learning Probabilistic Model Parameters 11. Learning Probabilistic Model Structure 12. Unsupervised Learning and Reinforcement Learning Part 3: Emergent Intelligence 13. Evolutionary Computation 14. Swarm Intelligence Part 4: Neural Intelligence 15. Neural Networks and Deep Learning Part 5: Language Understanding 16. Natural Language Understanding
At many universities courses on arti cial intelligence (AI) are offered, mainly for computer science students. This is very often a bit optimistic since this field also requires a sound mathematical background. Furthermore, there is now an increasing rumor about the problems, dangers etc. that may appear. In this field this textbook is an excellent contribution to avoid these discussions and make artificial intelligence more and more a practicable field!
-Christian Postho, St. Augustine