Includes bibliographical references and index.

Preface; Chapter 1: Introduction and Overview; Chapter 2: The HP Definition of Causality; 2.1 Causal Models; 2.2 A Formal Definition of Actual Cause; 2.3 Examples; 2.4 Transitivity; 2.5 Probability and Causality; 2.6 Sufficient Causality; 2.7 Causality in Nonrecursive Models; 2.8 AC2(bo) vs -- AC2(bu); 2.9 Causal Paths; 2.10 Proofs; Chapter 3: Graded Causation and Normality; 3.1 Defaults, Typicality, and Normality; 3.2 Extended Causal Models; 3.3 Graded Causation; 3.4 More Examples; 3.5 An Alternative Approach to Incorporating Normality; Chapter 4: The Art of Causal Modeling.

4.1 Adding Variables to Structure a Causal Scenario4.2 Conservative Extensions; 4.3 Using the Original HP Definition Instead of the Updated Definition; 4.4 The Stability of (Non- )Causality; 4.5 The Range of Variables; 4.6 Dependence and Independence; 4.7 Dealing With Normality and Typicality; 4.8 Proofs; Chapter 5: Complexity and Axiomatization; 5.1 Compact Representations of Structural Equations; 5.2 Compact Representations of the Normality Ordering; 5.3 The Complexity of Determining Causality; 5.4 Axiomatizing Causal Reasoning; 5.5 Technical Details and Proofs.

Chapter 6: Responsibility and Blame6.1 A Naive Definition of Responsibility; 6.2 Blame; 6.3 Responsibility, Normality, and Blame; Chapter 7: Explanation; 7.1 Explanation: The Basic Definition; 7.2 Partial Explanations and Explanatory Power; 7.3 The General Definition of Explanation; Chapter 8: Applying the Definitions; 8.1 Accountability; 8.2 Causality in Databases; 8.3 Program Verification; 8.4 LastWords; References; Index.

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A new approach for defining causality and such related notions as degree of responsibility, degrees of blame, and causal explanation.

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