Foundations of Artificial Intelligence: Intelligent Agents, Problem Solving, Search Algorithms, and Constraint Satisfaction (Artificial Intelligence Series)

E S, Lakshmi

ISBN 13: 9798187992560

Published by Independently published, 2026

About this Item

Print on Demand.

Seller Inventory # I-9798187992560

Bibliographic Details

• Title: Foundations of Artificial Intelligence: Intelligent Agents, Problem Solving, Search Algorithms, and Constraint Satisfaction (Artificial Intelligence Series)
• Publisher: Independently published
• Publication Date: 2026
• Language: English
• ISBN 13: 9798187992560
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Foundations of Artificial Intelligence

"The journey to intelligent systems begins with a strong foundation."

Artificial Intelligence (AI) is transforming industries, revolutionizing decision-making, and redefining the future of technology. Whether you're an engineering student, an educator, or an aspiring AI professional, understanding the core principles of AI is essential before exploring advanced topics such as Machine Learning, Deep Learning, and Generative AI.

Foundations of Artificial Intelligence is the first volume in the Artificial Intelligence Series, designed to provide a structured and comprehensive introduction to the fundamental concepts of AI. The book emphasizes conceptual clarity through intuitive explanations, real-world examples, worked illustrations, and step-by-step algorithm analysis.

Rather than presenting algorithms as isolated topics, this book explains why they are needed, how they work, where they are applied, and how to implement them, making it an ideal companion for both classroom learning and self-study.

What You'll Learn

Introduction to Artificial Intelligence

AI Problems and Intelligent Agents

Agents and Environments

Problem Formulation and Problem Spaces

Problem-Solving Agents

Uninformed Search Algorithms

• Breadth-First Search (BFS)
• Depth-First Search (DFS)
• Iterative Deepening Search

Heuristic Search Techniques

• Hill Climbing
• Generic Best-First Search
• Greedy Best-First Search
• A* Search Algorithm

Constraint Satisfaction Problems

• Backtracking Search
• Local Search

Key Features

• Concept-driven learning with intuitive explanations

• Step-by-step algorithm walkthroughs

• Flowcharts and illustrative diagrams

• Worked examples with detailed solutions

• Pseudocode for every major algorithm

• C programming implementations

• Time and space complexity analysis

• Practical applications and real-world examples