PROBABILISTIC AND CAUSAL LOGICS
Logics that integrate probability, uncertainty, and causation into formal reasoning: systems that attach degrees of belief or chance to formulas, combine logic with probabilistic models, or formalize causal and counterfactual inference. Degree here means probability, distinguishing these systems from the truth-degree logics of the many-valued subdivision.
Entries include the probability foundations (probability theory, probabilistic logic), the logic-probability combinations (probabilistic and Bayesian logic, Markov logic networks, probabilistic graphical models, probabilistic and stochastic logic programming, ProbLog), the uncertainty formalisms (imprecise probability, Dempster-Shafer theory, possibility theory, ranking theory, maximum entropy, conditional logic, Adams' probability logic, information-theory logic, expected-value logic), the stochastic temporal logics (continuous stochastic logic, stochastic logic), and the causal strand (causal inference, interventionist and counterfactual causation, probabilistic argumentation).