My new book, Introduction to Artificial Intelligence: Agents, Learning, and the Limits of Both, is now available on Amazon in Kindle, paperback, and hardcover editions.
I wrote it for readers who want to understand how AI works, rather than stop at what a system can produce. The book builds from first principles, using small, checkable examples to explain the mechanisms and the assumptions behind them. The mathematics is part of the explanation, not something to skip over.
What the book covers
Across ten chapters, the book covers search and reasoning, probability and machine learning, neural networks, computer vision, natural language processing, generative AI, reinforcement learning, intelligent agents, and AI ethics and safety.
These topics belong together. Search and reasoning help explain how a system chooses among possible actions. Probability gives us a way to work with uncertainty. Machine learning introduces systems that learn patterns from data. Those foundations make it easier to understand the language models and agents that receive so much attention today.
Figures and worked examples support the explanations. Each chapter also includes a summary, further reading, and review questions for independent study or use in teaching.
Why the limits matter
The subtitle, Agents, Learning, and the Limits of Both, reflects the book’s approach. Understanding a method includes understanding the conditions under which it works and where its assumptions stop being useful.
A model’s output can look convincing without being correct. An agent can take actions without having a reliable understanding of their consequences. Learning about AI should help readers examine those distinctions, not just recognize the names of algorithms.
The book treats uncertainty, ethics, and safety as part of understanding AI. They belong in the discussion alongside the technical methods.
Who it is for
I wrote this book for students, software engineers, and technically curious readers. Students can use it to build a foundation in the field. Engineers can connect familiar software concepts to AI methods. Readers studying on their own can work through the examples and use the review questions to check their understanding.
My aim is to make the reasoning visible: what a method does, what it assumes, and how to judge its results.
Get the book
Introduction to Artificial Intelligence: Agents, Learning, and the Limits of Both was published on September 27, 2026. The English-language first edition is listed at 804 pages.
View the book on Amazon to read the sample and choose the Kindle, paperback, or hardcover edition.