Am höchsten bewertete kritische Rezension
13 Personen fanden diese Informationen hilfreich
am 13. Dezember 1999
While R&N's coverage of topics in Artificial Intelligence is no doubt encyclopedic, several problems exist with the book:
1) The textbook is awfully traditional and only mentions in passing newer trends in AI. For example, case-based reasoning (or the "Yale view of AI") is mentioned, but not covered. Because AI is a new and rapidly changing field, and because AI paradigms are usually based on a small set of ontological assumptions, I believe it would not be too difficult for students to understand new paradigms. Obviously this should be a high pedagogical priority.
2) The textbook is rather condescending, with the authors strongly imposing their viewpoints. In other words, the authors are a little too dogmatic and that is reflected in the text. For example, they sometimes go about ranking paradigms.
3) The textbook is sometimes rather ambiguous when explicating certain paradigms, and the end-of-chapter problems are very, very ambiguous. One of the justifications for unclear questions is to get people thinking, but when the theoretical explications are already ambiguous it defeats the whole purpose.
4) The philosophical sections in R&N are rather naive and superficial.
In spite of its obvious shortcomings, R&N has been tremendously useful to me, and I recommend it as a reference. The good news, I've heard, is that a new edition of R&N is coming out next year where these problems are eliminated.