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Artificial Intelligence

Author(s): Saroj Kaushik

ISBN: 9789355730428

2nd Edition

Copyright: 2022

India Release: 2022

₹895

Binding: Paperback

Pages: 712

Trim Size: 241 x 181 mm

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The second edition of the Artificial Intelligence book is a comprehensive resource for undergraduate and graduate students, covering core AI topics like search, planning, knowledge representation, expert systems, and uncertainty handling. It also explores advanced areas such as machine learning, fuzzy logic, neural networks, evolutionary computing, and NLP. Organized into 16 chapters across six units, it includes pedagogical tools and examples for better understanding. The book uses PROLOG to teach AI programming aligned with human problem-solving logic. With 40% more content than typical UG curricula, it’s ideal for full-semester AI courses and professionals seeking deeper AI knowledge.

  • The approach has been kept simple and student-friendly to ensure that every student can derive maximum possible knowledge from the book.
  • Each chapter incorporates numerous pedagogical features, such as solved examples, detailed illustrations, tables, algorithms, and end-of-chapter exercises that supplement the topics presented.
  • The presence of solved examples and algorithms aids in sharpening students' understanding of the concepts covered.
  • Includes a license key for our digital learning app, CENGAGE Digital App, that provides access to complete topics: Introduction to Intelligent Agents and Advanced Knowledge Representation Techniques

 

1. Artificial Intelligence Fundamentals

UNIT 1: PROBLEM SOLVING

2. State-Space Searches 

3. Problem Reduction and Game Playing

UNIT 2: LOGIC CONCEPTS AND LOGIC PROGRAMMING

4. Logical Reasoning

5. Prolog Programming

UNIT 3: PLANNING, KNOWLEDGE REPRESENTATION AND EXPERT SYSTEM

6. Advanced Problem-Solving Paradigm: Planning 

7. Knowledge Representation 

8. Expert System and Applications 

UNIT 4: HANDLING UNCERTAINTY AND FUZZY KNOWLEDGE

9. Uncertainty Measure: Probability Theory

10. Fuzzy Sets and Fuzzy Logic

UNIT 5: MACHINE LEARNING PARADIGMS

11. Machine Learning

12. Artificial Neural Networks 

13. Evolutionary Computation

UNIT 6: TRADITIONAL AND LATEST PERSPECTIVES OF NATURAL LANGUAGE PROCESSING (NLP)

14. Traditional NLP

15. NLP Application Pipeline

16. Advanced NLP with Deep Neural Networks

Saroj Kaushik

Saroj Kaushik, PhD (Computer Science) from Indian Institute of Technology Delhi is Retired Professor of CSE at Indian Institute of Technology Delhi, India.