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Artificial intelligence is a hard subject to learn. I have written a book to make it easier. I explain difficult concepts in a simple, concrete way. I have organized the material in a new and (I feel) clearer way, a way in which the chapters are in a logical sequence and not just unrelated topics. I believe that with this book, readers can learn the key concepts of artificial intelligence faster and better than with other books. This book is intended for all first courses in artificial intelligence at the undergraduate or graduate level, requiring background of only a few computer science courses. It can also be used on one's own.

Students often complain that while they understand the terminology of artificial intelligence, they don't have a gut feeling for what's going on or how you apply the concepts to a situation. One cause is the complexity of artificial intelligence. Another is the unnecessary baggage, like overly formal logical calculi, that some books and teachers saddle students with. But an equally important cause is the often poor connection made between abstract concepts and their use. So I considered it essential to integrate practical programming examples into this book, in the style of programming language and data structures books. (I stress practical, not missionaries and cannibals, definitions of "grandfather", or rules for identifying animals in zoos--at least rarely.) This book has about 500 chunks of code. Clear, concrete formalization of artificial intelligence ideas by programs and program fragments is all the more critical today with commercialization and media discovery of the field, which has caused a good deal of throwing around of artificial intelligence terms by people who don't understand them.

But artificial intelligence is a tool for complex problems, and its program examples can easily be forbiddingly complicated. Books attempting to explain artificial intelligence with examples from the programming language Lisp have repeatedly demonstrated this. But I have come to see that the fault lies more with Lisp than with artificial intelligence. Lisp has been the primary language of artificial intelligence for many years, but it is a low-level language, too low for most students. Designed in the early 1960s, Lisp reflects the then-primitive understanding of good programming, and requires the programmer to worry considerably about actual memory references (pointers). Furthermore, Lisp has a weird, hard-to-read syntax unlike that of any other programming language. To make matters worse, the widespread adoption of Common Lisp as a de facto standard has discouraged research on improved Lisps.

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