INTRODUCTION TO ARTIFICIAL INTELLIGENCE WOLFGANG ERTEL PDF

English xi, pages : 24 cm "This concise and accessible textbook supports a foundation or module course on A. The book presents concrete algorithms and applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks and reinforcement learning. Topics and features: presents an application-focused and hands-on approach to learning the subject; provides study exercises of varying degrees of difficulty at the end of each chapter, with solutions given at the end of the book; supports the text with highlighted examples, definitions, and theorems; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; contains an extensive bibliography for deeper reading on further topics; supplies additional teaching resources, including lecture slides and training data for learning algorithms, at an associated website. Propositional Logic.

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Start your review of Introduction to Artificial Intelligence Write a review Jul 02, Bojan Tunguz rated it really liked it Artificial Intelligence is by now a relatively old field, having originated in the early days of the digital computer revolution. However, it has had a very rocky and turbulent history, going through several cycles of overblown expectations followed by almost equally dramatic swings towards disillusionment and skepticism. In recent years, though, it has matured into a very solid and practical discipline that exercises an ever growing importance across a wide breadth of technologies and Artificial Intelligence is by now a relatively old field, having originated in the early days of the digital computer revolution.

In recent years, though, it has matured into a very solid and practical discipline that exercises an ever growing importance across a wide breadth of technologies and professions. We increasingly take speech recognition, handwriting recognition, and natural language search for granted. Basic familiarity with what Artificial Intelligence is, and what tools and techniques fall under its domain, are becoming ever important aspect of a variety of professions and occupations.

There is no shortage of books and resources on Artificial Intelligence. However, most of them fall squarely into two main camps: discursive overviews for the general audience, and highly advanced textbooks requiring deep familiarity with many advanced technical concepts.

The book is organized somewhat chronologically along the lines of topics that have historically formed the main organizing principles for the study of Artificial Intelligence - first and second order logic, propositional calculus, PROLOG, machine learning, neural networks. I would have also liked a substantially more material on machine learning and neural nets, maybe at the expense of the earlier chapters.

These topics have a lot of practical applications today, and seem to be the guiding paradigms for Artificial Intelligence as a whole for a foreseeable future. Nonetheless, the book overall is very readable and relevant. One of the most valuable aspects of this book are the worked out examples and numerous solved exercises.

Working through problems is, by far, the best way to learn any new material, and this book provides the reader with numerous and wide-ranging opportunity to do exactly that.

Overall, this is a very well written and pedagogical book that fills an important niche in the Artificial Intelligence educational literature. Highly recommended. This book spent a lot more time discussing logic and not doing a very good job of it. Its been a long time since I did symbolic logic so I had a hard time remembering what the symbols and operators meant. As a result, I didnt follow many of the authors discussions.

Expensive book, not worth the price. Not what I was expecting.

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