Artificial Intelligence: Reasoning, Learning and Expert Systems: Knowledge Representation, Reasoning Under Uncertainty, Learning and Knowledge Engineering (Artificial Intelligence Series)

Knowledge Representation, Reasoning Under Uncertainty, Learning and Knowledge Engineering

Artificial Intelligence is a rapidly evolving field that explores how intelligent systems represent knowledge, reason, learn, and solve complex problems. This volume provides a structured introduction to advanced concepts in Artificial Intelligence, with a focus on knowledge representation, reasoning under uncertainty, machine learning fundamentals, and expert systems.

Designed for undergraduate engineering students, computer science learners, and readers seeking a deeper understanding of AI principles, this book bridges theoretical foundations with practical applications.

What You Will Learn

• Advanced Knowledge Representation and Reasoning: Explore knowledge representation issues, non-monotonic reasoning, and alternative knowledge representation schemes.

• Reasoning Under Uncertainty: Understand probability, Bayesian reasoning, Bayes' rule, knowledge representation in uncertain domains, and Bayesian networks.

• Learning in Artificial Intelligence: Study rote learning, learning by taking advice, learning in problem-solving environments, learning from examples, Winston's learning program, and decision trees.

• Expert Systems and Knowledge Engineering: Understand how domain knowledge is represented and utilized, the architecture of expert systems, expert system shells, explanation facilities, and knowledge acquisition.

Key Features

• Clear and systematic coverage of essential AI concepts.

• Structured explanations that support conceptual understanding.

• A foundation for exploring intelligent reasoning and learning mechanisms.

• Relevant to computer science and engineering curricula.

• Suitable for academic study, teaching, examination preparation, and independent learning.

Who Should Read This Book?

This book is intended for undergraduate and postgraduate students in Computer Science and Engineering, Artificial Intelligence, Information Technology, and related disciplines. Faculty members, educators, and aspiring AI practitioners may also find it useful as a reference for understanding the fundamental principles behind intelligent systems.

Whether you are studying Artificial Intelligence as an academic subject or strengthening your understanding of intelligent reasoning and knowledge engineering, this book offers a systematic pathway into the concepts that shape modern AI.

A valuable addition to your Artificial Intelligence textbook collection, bringing together reasoning, learning, and expert systems in one comprehensive volume.