Higher Education
Author(s): Saroj Kaushik
ISBN: 9789355730428
2nd Edition
Copyright: 2022
India Release: 2022
Binding: Paperback
Pages: 712
Trim Size: 241 x 181 mm
This second edition of Artificial Intelligence is designed to provide comprehensive material for undergraduate and graduate students on the vast and fast-growing subject of Artificial Intelligence. This book has been written keeping in mind the syllabi designed for courses on AI in various technical institutions and universities in India and abroad. It can serve as a textbook for one full-semester course on AI. It will also provide study material to computer professionals who wish to expand their knowledge on AI.
The book is divided into 6 units with each unit containing related chapters. There are overall 16 chapters. Compared with the syllabi of UG programmes in Indian universities, there is about 40% extra material that might be useful for advanced AI courses. The main topics covered in the book include problem-solving using intelligent searches and planning, knowledge representation techniques, game playing, first-order predicate logic and programming language PROLOG (programming in logic), uncertainty handling, expert systems, knowledge representation, etc. The language PROLOG (declarative language) has been used throughout the book which I am very passionate about as it helps user to code programs for problems using AI techniques with a clear understanding of underline and natural thought processes of human ways of solving problems.
In addition, some advanced topics such as machine learning, fuzzy logic, artificial neural networks, evolutionary computing, and natural language processing have been included in detail. Each chapter in the book has been carefully developed with the help of several pedagogical features. A huge effort has been put in to explain every concept discussed in the book with the help of examples as far as possible. Pseudo-algorithms for various methods and techniques are included throughout the text to increase the comprehensibility of the topics and demonstrate their applications.
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. She was faculty at IITD (1980–2019) with teaching experience of about four decades. She taught the course on AI and other computer science courses at UG and PG levels. Prof. Kaushik has published more than 100 research papers in national and international journals and conferences. She was visiting professor at MUM University, Fairfield, Iowa, USA, for teaching AI course and guiding PG students for their projects in 2008 fall. She has supervised 90+ UG and PG major projects and successfully guided many PhD students. Dr Kaushik is Fellow member of IETE (Institution of Electronics and Telecommunication Engineers) India and life member of CSI (Computer Society of India).
