Fundamentals of Artificial Intelligence: Concepts, Algorithms and Applications

Fundamentals of Artificial Intelligence offers a structured and comprehensive overview of the key concepts and techniques that form the basis of AI. The book begins with an introduction to intelligent agents, problem-solving methods, and search algorithms, including uninformed and informed search strategies.
It further explores knowledge representation techniques such as logic, semantic networks, and ontologies, along with reasoning methods that enable machines to make decisions. The text covers core areas of machine learning, including supervised and unsupervised learning, as well as an introduction to neural networks and deep learning concepts.
Additional topics include natural language processing, computer vision, robotics, and expert systems, providing readers with insights into major AI application domains. The book also discusses ethical issues, bias in AI systems, and the challenges of building reliable and transparent models. With practical examples, diagrams, and real-world applications, this book is suitable for undergraduate and postgraduate students in computer science, information technology, and related fields. It serves as both a foundational textbook and a stepping stone for advanced studies in artificial intelligence.