The Elements of Artificial Intellig...
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Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less
Book Summary
A classic textbook on artificial intelligence by Steven L. Tanimoto, this used copy offers comprehensive coverage of core AI concepts, from search and knowledge representation to machine learning. Despite signs of wear, it remains a valuable resource for students and professionals seeking a foundational understanding of AI principles and techniques.
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About The Elements of Artificial Intellig...
The Elements of Artificial Intelligence by Steven L. Tanimoto is a foundational textbook that introduces the core concepts and techniques of AI. It covers essential topics such as problem-solving through search, knowledge representation, reasoning, natural language processing, and machine learning. The book balances theoretical foundations with practical algorithms, making it suitable for computer science students and professionals new to the field. This used copy may contain notes and highlighting, and the spine may show wear, but the content remains intact and useful for learning. Tanimoto's clear explanations and examples help readers grasp complex ideas, making it a solid choice for anyone building a base in AI, even if newer editions or more modern texts exist.
Who should read The Elements of Artificial Intellig...?
This book is ideal for undergraduate or graduate students in computer science taking an introductory AI course, as well as professionals from other fields seeking a structured introduction to AI concepts. It suits self-learners who prefer a textbook approach with theoretical depth and algorithmic detail. Readers should have some programming background and basic knowledge of data structures and algorithms. It is also useful for instructors looking for a classic text to supplement modern materials.
Pros & Cons
Pros
- ✓ Comprehensive coverage of fundamental AI topics
- ✓ Clear explanations of complex concepts
- ✓ Includes practical algorithms and examples
- ✓ Suitable for both classroom use and self-study
- ✓ Affordable used copy despite some wear
Cons
- ✗ May lack coverage of recent AI advancements
- ✗ Some notations or examples may feel dated
- ✗ Used copy may have notes and highlighting
- ✗ Spine wear could affect durability
- ✗ Not a substitute for modern, up-to-date resources
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Frequently asked questions
Is this book still relevant given recent AI advances?
While it may not cover the latest deep learning techniques, the fundamental concepts like search, knowledge representation, and basic machine learning remain relevant and provide a strong foundation.
What condition is this used copy in?
The description notes pages may have notes and highlighting, and the spine may show signs of wear, but the book is complete and readable.
Do I need programming experience to understand this book?
Some programming background, especially in languages like Lisp or Prolog, is helpful, but the book explains concepts clearly enough for motivated beginners.
Is this suitable for self-study?
Yes, the book includes exercises and examples that facilitate self-learning, though supplementary online resources may enhance understanding.
How does this compare to Russell & Norvig's book?
Tanimoto's book is more concise and focuses on classical AI, while Russell & Norvig is more comprehensive and up-to-date, often considered the standard text.
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