Axiomatizing Causal Reasoning

dc.creatorHalpern, Joseph Y.
dc.date2000-05-30
dc.date.accessioned2026-07-07T03:16:15Z
dc.date.available2026-07-07T03:16:15Z
dc.descriptionCausal models defined in terms of a collection of equations, as defined by Pearl, are axiomatized here. Axiomatizations are provided for three successively more general classes of causal models: (1) the class of recursive theories (those without feedback), (2) the class of theories where the solutions to the equations are unique, (3) arbitrary theories (where the equations may not have solutions and, if they do, they are not necessarily unique). It is shown that to reason about causality in the most general third class, we must extend the language used by Galles and Pearl. In addition, the complexity of the decision procedures is characterized for all the languages and classes of models considered.
dc.descriptionAn earlier version of this paper appeared in UAI '98
dc.identifierhttps://arxiv.org/abs/cs/0005030
dc.identifierhttp://arxiv.org/abs/cs/0005030
dc.identifierJournal of AI Research, Vol. 12, 2000, pp. 317--337
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/30278
dc.subjectArtificial Intelligence
dc.subjectLogic in Computer Science
dc.subjectI.2.4; F.4.1
dc.titleAxiomatizing Causal Reasoning
dc.typetext

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