"Artificial Intelligence and Intelligent Systems" by NP Padhy is a comprehensive textbook that covers the fundamental concepts and techniques of Artificial Intelligence and Intelligent Systems. The book is designed for undergraduate and postgraduate students of computer science, electronics, and electrical engineering. It provides a thorough understanding of the subject matter, with a focus on theoretical foundations, practical applications, and recent advancements.

Since this is not a math problem $$ isn't required here.

Why? Because Dr. N.P. Padhy’s book has become a cornerstone text for understanding not just the theoretical underpinnings of AI, but also the practical architecture of Intelligent Systems —a field that merges AI with real-world problem-solving.

This article provides an in-depth review of the book, including its full table of contents, target audience, key features, and how to legally access it. Whether you are an undergraduate student looking for a course textbook or a self-learner exploring AI, this guide will help you understand why this book is worth your time.

: Detailed analysis of uninformed (BFS, DFS) and informed (A*, Best-First Search) techniques used in problem-solving. Knowledge Representation

Published by Oxford University Press, Artificial Intelligence and Intelligent Systems by Dr. N.P. Padhy (a distinguished professor and academic administrator) bridges the gap between theoretical AI concepts and practical system design. The book is specifically engineered to cater to undergraduate and postgraduate students of computer science, information technology, and electrical engineering.

You might wonder if a 2005 textbook is relevant in the era of Large Language Models (LLMs) and Generative AI. Absolutely. Here is why: