Introduction to Artificial Intelligence

1. Front Matter

   Pages i-xiv

   PDF

2. Introduction

   • Wolfgang Ertel

   Pages 1-21

3. Propositional Logic

   • Wolfgang Ertel

   Pages 23-38

4. First-order Predicate Logic

   • Wolfgang Ertel

   Pages 39-64

5. Limitations of Logic

   • Wolfgang Ertel

   Pages 65-73

6. Logic Programming with PROLOG

   • Wolfgang Ertel

   Pages 75-90

7. Search, Games and Problem Solving

   • Wolfgang Ertel

   Pages 91-124

8. Reasoning with Uncertainty

   • Wolfgang Ertel

   Pages 125-174

9. Machine Learning and Data Mining

   • Wolfgang Ertel

   Pages 175-243

10. Neural Networks

    • Wolfgang Ertel

    Pages 245-287

11. Reinforcement Learning

    • Wolfgang Ertel

    Pages 289-311

12. Solutions for the Exercises

    • Wolfgang Ertel

    Pages 313-338

13. Back Matter

    Pages 339-356

    PDF

This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning.

Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayes’ theorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW).

Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material.

• Artificial Intelligence
• Agents
• Logic
• Search
• Reasoning with Uncertainty
• Machine Learning
• Neural Networks

• Hochschule Ravensburg-Weingarten, Weingarten, Germany

  Wolfgang Ertel

Dr. Wolfgang Ertel is a professor at the Institute for Artificial Intelligence at the Ravensburg-Weingarten University of Applied Sciences, Germany.