A logical notion of conditional independence: Properties and applications

Artificial Intelligence

Volumn 97, Issue 1-2, 1997, Pages 45-82

  Darwiche, Adnan ^a  

^a AMERICAN UNIVERSITY OF BEIRUT   (Lebanon)

Author keywords

Causal networks; Graphoids; Independence; Logic; Probability; Pruning knowledge bases; Relevance; Structure based reasoning

Indexed keywords

ALGORITHMS; DATABASE SYSTEMS; GRAPH THEORY; GRAPHIC METHODS; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; PROBABILISTIC LOGICS;

STRUCTURED BASED REASONING;

ARTIFICIAL INTELLIGENCE;

EID: 0031331431     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0004-3702(97)00042-8     Document Type: Article

References (26)

1. B.D. D'Ambrosio, Local expression languages for probabilistic dependence, Internat. J. Approximate Reasoning 11 (1994) 1-15.
2. A. Darwiche, A symbolic generalization of probability theory, Ph.D. Thesis, Stanford University, Stanford, CA (1992).
3. A. Darwiche, Conditioning algorithms for exact and approximate inference in causal networks, in: Proceedings 11th Conference on Uncertainty in Artificial Intelligence (UAI) (1995) 99-107.
4. A. Darwiche, Model-based diagnosis using causal networks, in: Proceedings IJCAI-95, Montreal, Que. (1995) 211-217.
5. A. Darwiche and J. Pearl, Symbolic causal networks, in: Proceedings AAAI-94, Seattle, WA (1994) 238-244.
6. J. de Kleer, An assumption-based TMS, Artificial Intelligence 28 (1986) 127-162.
7. J. de Kleer, A.K. Mackworth and R. Reiter, Characterizing diagnoses and systems, Artificial Intelligence 56 (1992) 197-222.
8. R. Dechter and A. Dechter, Belief maintenance in dynamic constraint networks, in: Proceedings AAAI-88, St. Paul, MN (1988) 37-42.
9. R. Dechter and A. Dechter, Structure-driven algorithms for truth maintenance, Artificial Intelligence 82 (1996) 1-20.
10. R. Dechter and J. Pearl, Directed constraint networks: A relational framework for causal modeling, in: Proceedings IJCAI-91, Sydney, Australia (1991) 1164-1170.
11. P. Gärdenfors, Knowledge in Flux: Modeling the Dynamics of Epistemic States (MIT Press, Cambridge, MA, 1988).
12. H. Geffner and J. Pearl, An improved constraint-propagation algorithm for diagnosis, in: Proceedings IJCAI-87, Milan, Italy (1987) 1105-1111.
13. R. Greiner and D. Subramanian, Relevance, in: Working Notes, AAAI-94 Fall Symposium Series, New Orleans, LA (1994).
14. F.V. Jensen, S.L. Lauritzen and K.G. Olesen, Bayesian updating in recursive graphical models by local computation, Comput. Statist. Quart. 4 (1990) 269-282.
15. A.Y. Levy, Irrelevance reasoning in knowledge based systems, Ph.D. Thesis, Stanford University, Stanford, CA (1993).
16. A. Levy, I.S. Mumick and Y. Sagiv, Query optimization by predicate movearound, in: Proceedings 20th VLDB Conference, Santiago, Chile (1994).
17. A.Y. Levy and Y. Sagiv, Queries independent of updates, in: Proceedings 19th VLDB Conference, Dublin, Ireland (1993) 171-181.
18. Z. Li and B.D. D'Ambrosio, Efficient inference in Bayes networks as a combinatorial optimization problem, Internat. J. Approximate Reasoning 11 (1994) 55-81.
19. J. Pearl, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference (Morgan Kaufmann, San Mateo, CA, 1988).
20. M.A. Peot and R.D. Shachter, Fusion and propagation with multiple observations in belief networks, Artificial Intelligence 48 (1991) 299-318.
21. R. Reiter and J. de Kleer, Foundations of assumption-based truth maintenance systems: preliminary report, in: Proceedings AAAI-87, Milan, Italy (1987) 183-188.
22. R. Shachter, S.K. Andersen and P. Szolovits, Global conditioning for probabilistic inference in belief networks, in: Proceedings 10th Conference on Uncertainty in AI, Seattle, WA (1994) 514-522.
23. D. Subramanian, A theory of justified reformulations, Ph.D. Thesis, Stanford University, Stanford, CA (1989).
24. D. Subramanian and M.R. Genesereth, The relevance of irrelevance, in: Proceedings IJCAI-87, Milan, Italy (1987) 416-422.
25. T. Verma and J. Pearl, Causal networks: semantics and expressiveness, in: Proceedings 4th Workshop on Uncertainty in AI, Minneapolis, MN (1988) 352-359.
26. N. Wilson, Generating graphoids from generalised conditional probability, in: Proceedings 10th Conference on Uncertainty in AI, Seattle, WA (1994) 583-590.