Axiomatizing causal reasoning

Authors
Citation
Jy. Halpern, Axiomatizing causal reasoning, J ARTIF I R, 12, 2000, pp. 317-337
Citations number
14
Categorie Soggetti
AI Robotics and Automatic Control
Journal title
JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH
ISSN journal
10769757 → ACNP
Volume
12
Year of publication
2000
Pages
317 - 337
Database
ISI
SICI code
1076-9757(2000)12:<317:ACR>2.0.ZU;2-3
Abstract
Causal models defined in terms of a collection of equations, as defined by Pearl, are axiomatized here. Axiomatizations are provided for three success ively more general classes of causal models: (1) the class of recursive the ories (those without feedback), (2) the class of theories where the solutio ns 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 (1997, 1998). In addi tion, the complexity of the decision procedures is characterized for all th e languages and classes of models considered.