A Logical Theory of Causality

A general formal theory of causal reasoning as a logical study of causal models, reasoning, and inference.

In this book, Alexander Bochman presents a general formal theory of causal reasoning as a logical study of causal models, reasoning, and inference, basing it on a supposition that causal reasoning is not a competitor of logical reasoning but its complement for situations lacking logically sufficient data or knowledge. Bochman also explores the relationship of this theory with the popular structural equation approach to causality proposed by Judea Pearl and explores several applications ranging from artificial intelligence to legal theory, including abduction, counterfactuals, actual and proximate causality, dynamic causal models, and reasoning about action and change in artificial intelligence.
            As logical preparation, before introducing causal concepts, Bochman describes an alternative, situation-based semantics for classical logic that provides a better understanding of what can be captured by purely logical means. He then presents another prerequisite, outlining those parts of a general theory of nonmonotonic reasoning that are relevant to his own theory. These two components provide a logical background for the main, two-tier formalism of the causal calculus that serves as the formal basis of his theory. He presents the main causal formalism of the book as a natural generalization of classical logic that allows for causal reasoning. This provides a formal background for subsequent chapters. Finally, Bochman presents a generalization of causal reasoning to dynamic domains.
 Preface xi
I LOGICAL PROLEGOMENA
1 A Two-Tier System of Causal Reasoning 
2 Mereological Semantics for Classical Logic
3 Assumption-Based Nonmonotonic Reasoning
II THE BASICS
4 Causal Calculus
5 Structural Equation Models
6 Indeterminate Causation
III EXPLANATORY CAUSAL REASONING
7 Abduction 
8 Actual Causality
9 Relative Causality
IV DYNAMIC CAUSAL REASONING
10 Causal Dynamic Formalisms
11 Dynamic Markov Assumption
12 Dynamic Causal Calculus
Bibliography
Index“Bochman applies ideas of logic-based artificial intelligence to the study of causation. This monograph is an excellent, self-contained description of his valuable research.”
—Vladimir Lifschitz, Gottesman Family Centennial Professor in Computer Sciences, University of Texas at AustinAlexander Bochman is Associate Professor in the Computer Science Department at Holon Institute of Technology in Holon, Israel.