Handbook of Logic in Artificial Intelligence: Logic Programming by Christopher John Hogger – A Foundational Reference fo

Introduction

The Handbook of Logic in Artificial Intelligence: Logic Programming by Christopher John Hogger is an authoritative volume that delves deep into the intersection of logic and artificial intelligence. As part of a prestigious five-volume series, this hardcover edition from OUP Oxford offers a rigorous exploration of logic programming, a foundational pillar of modern AI. For Indian students, researchers, and professionals in computer science and AI, this book serves as an indispensable resource for understanding how logical reasoning drives intelligent systems.

Book Overview

This volume is the fifth and concluding part of the Handbook of Logic in Artificial Intelligence series, designed to provide a comprehensive survey of logic's role in AI. Focused exclusively on logic programming, it brings together contributions from internationally renowned experts. The book examines the theoretical underpinnings, practical methodologies, and unifying themes that make logic programming a powerful paradigm for knowledge representation, automated reasoning, and problem-solving. It is a definitive reference that bridges abstract logic with real-world AI applications.

Key Highlights

• Authoritative Content: Edited by Christopher John Hogger, a respected figure in logic and computation, with chapters from leading global researchers.
• Comprehensive Scope: Covers the entire spectrum of logic programming, from foundational theory to advanced topics like non-monotonic reasoning and constraint logic programming.
• Monograph-Length Chapters: Each chapter is detailed and self-contained, offering deep insights suitable for advanced study.
• Emphasis on Unifying Themes: Highlights connections between different logic programming paradigms, aiding holistic understanding.
• Premium Hardbound Edition: A durable, high-quality print from OUP Oxford, ideal for academic libraries and personal collections.

Inside the Book

The book is structured around several major themes. It begins with the core principles of logic programming, including Horn clause logic and resolution-based proof procedures. Subsequent chapters explore extensions like negation as failure, disjunctive logic programming, and meta-programming. The volume also addresses practical aspects such as implementation techniques, semantics, and the integration of logic programming with databases and knowledge-based systems. Each chapter is rich with formal definitions, theorems, and examples that clarify complex concepts.

Key Topics

• Foundations of Logic Programming: Syntax, semantics, and proof theory of Horn clause logic.
• Negation and Non-Monotonic Reasoning: Handling incomplete information and default assumptions.
• Constraint Logic Programming: Combining logic with constraint solving for real-world problems.
• Meta-Programming and Reflection: Techniques for programs that manipulate other programs.
• Logic Programming and Databases: Deductive databases and query optimization.
• Implementation Strategies: Compilation, abstract machines, and parallel execution models.

Reader Benefits

Readers gain a deep, formal grounding in logic programming that is directly applicable to AI research and development. The book helps build a strong conceptual framework for understanding how logical inference can be mechanized. It also provides practical knowledge for designing and implementing logic-based systems, making it valuable for both theoretical exploration and applied projects. For Indian academics, this volume aligns well with advanced curricula in AI, computational logic, and knowledge engineering.

Learning Outcomes

• Master the theoretical foundations of logic programming, including syntax, semantics, and proof procedures.
• Understand how to represent knowledge using Horn clauses and handle negation effectively.
• Learn to apply constraint logic programming to optimization and scheduling problems.
• Gain insights into meta-programming techniques for building flexible AI systems.
• Develop the ability to critically evaluate and extend logic programming paradigms.

Who Should Read

This book is ideal for postgraduate students and researchers in artificial intelligence, computer science, and logic. It is also highly relevant for professionals working in knowledge representation, automated reasoning, and software verification. Faculty members designing advanced courses in AI or logic programming will find it a valuable reference. Anyone with a solid background in discrete mathematics and basic logic will benefit from this deep dive into logic programming.

About the Author

Christopher John Hogger is a renowned British computer scientist and logician, known for his contributions to logic programming and automated reasoning. He has been a faculty member at Imperial College London and has authored several influential works on logic and computation. His editorial leadership ensures that this handbook maintains the highest standards of academic rigor and clarity.

About the Publisher

OUP Oxford (Oxford University Press) is one of the world's oldest and most respected academic publishers. With a legacy of excellence spanning over five centuries, OUP is synonymous with authoritative scholarship in science, technology, and the humanities. This hardcover edition reflects OUP's commitment to producing high-quality, enduring academic works.

Conclusion

The Handbook of Logic in Artificial Intelligence: Logic Programming is an essential acquisition for any serious AI library. It offers a comprehensive, rigorous, and well-organized treatment of logic programming that will benefit students, researchers, and practitioners alike. Whether you are exploring the theoretical depths of logical inference or building practical AI systems, this volume provides the clarity and depth you need. Order your copy from Bookshops.in today and add a cornerstone reference to your collection.