Cambridge Tracts in Theoretical Computer Science Séries

Focusing on a specific type system, this book offers a detailed introduction to type theory, essential for designing higher-level programming languages like ML. It explores the connection between type systems and propositional logic, while providing an in-depth examination of the type-checking algorithm foundational to these systems. The author presents the material with rigorous yet accessible mathematics, making it an ideal resource for computer scientists seeking to understand type theory at an introductory level.

The book introduces a novel framework that enhances the type notation used in functional programming languages by incorporating a specific notation to differentiate between run-time and compile-time behaviors. This extension aims to improve clarity and understanding of type systems, facilitating better programming practices and error detection in functional languages.

Reasoning under uncertainty, that is, making judgments with only partial knowledge, is a major theme in artificial intelligence. Professor Paris provides here an introduction to the mathematical foundations of the subject. The author presents the key results on the subject, and formalizes within a unified framework the main contemporary approaches and assumptions. He concentrates on giving clear mathematical formulations, analyses, justifications, and consequences of the main theories about uncertain reasoning.