Uncertainty, Causality, and Conditionals

Content

• Bayesian epistemology
• Causal models (Pearl), actual causality (Halpern)
• D-separation
• Do-calculus
• IC, PC algorithm for acquiring causal models
• Intervention
• Counterfactual conditionals in the do-calculus
• Multivalued logics for conditionals
• Knowledge revision and (counterfactual) conditionals
• Nonmonotonic logics and preference semantics
• Probabilistic logics