Introduction to Artificial Intelligence

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This engaging textbook provides a concise introduction to artificial intelligence (AI), covering key subdisciplines and practical algorithms. The revised second edition includes new material on deep learning, enhancing its relevance. It adopts an application-focused, hands-on approach, supported by supplementary teaching resources on an associated website. Readers will find numerous study exercises, highlighted examples, definitions, theorems, and illustrative cartoons throughout. Key topics include predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning, neural networks, and reinforcement learning. The book also explores recent advancements in deep learning, showcasing neural network applications in creative content generation like text, music, and art. Additionally, it examines the performance evaluation of clustering algorithms and provides practical examples of Bayes’ theorem in everyday life. The discussion on search algorithms includes cycle checks, route planning for navigation systems, and an introduction to Monte Carlo Tree Search. A section on AI and society addresses the implications of AI on employment and transportation. This easy-to-read textbook is ideal for foundation courses in AI, offering an excellent overview for computer science students and those in technical disciplines, requiring only a high-school level of mathematics.