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.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 TechniquesTable of Contents:1. Artificial Intelligence FundamentalsUNIT 1: PROBLEM SOLVING2. State-Space Searches 3. Problem Reduction and Game PlayingUNIT 2: LOGIC CONCEPTS AND LOGIC PROGRAMMING4. Logical Reasoning5. Prolog ProgrammingUNIT 3: PLANNING, KNOWLEDGE REPRESENTATION AND EXPERT SYSTEM6. Advanced Problem-Solving Paradigm: Planning 7. Knowledge Representation 8. Expert System and Applications UNIT 4: HANDLING UNCERTAINTY AND FUZZY KNOWLEDGE9. Uncertainty Measure: Probability Theory10. Fuzzy Sets and Fuzzy LogicUNIT 5: MACHINE LEARNING PARADIGMS11. Machine Learning12. Artificial Neural Networks 13. Evolutionary ComputationUNIT 6: TRADITIONAL AND LATEST PERSPECTIVES OF NATURAL LANGUAGE PROCESSING (NLP)14. Traditional NLP15. NLP Application Pipeline16. Advanced NLP with Deep Neural Networks