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  1. An assumption-based TMS.Johan de Kleer - 1986 - Artificial Intelligence 28 (2):127-162.
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  • Evidential reasoning using stochastic simulation of causal models.Judea Pearl - 1987 - Artificial Intelligence 32 (2):245-257.
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  • A theory of diagnosis from first principles.Raymond Reiter - 1987 - Artificial Intelligence 32 (1):57-95.
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  • Probabilistic Horn abduction and Bayesian networks.David Poole - 1993 - Artificial Intelligence 64 (1):81-129.
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  • Fusion, propagation, and structuring in belief networks.Judea Pearl - 1986 - Artificial Intelligence 29 (3):241-288.
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  • Depth-first iterative-deepening.Richard E. Korf - 1985 - Artificial Intelligence 27 (1):97-109.
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  • Gibbs sampling in Bayesian networks.Tomas Hrycej - 1990 - Artificial Intelligence 46 (3):351-363.
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  • The use of design descriptions in automated diagnosis.Michael R. Genesereth - 1984 - Artificial Intelligence 24 (1-3):411-436.
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  • Diagnosing multiple faults.Johan de Kleer & Brian C. Williams - 1987 - Artificial Intelligence 32 (1):97-130.
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  • Characterizing diagnoses and systems.Johan de Kleer, Alan K. Mackworth & Raymond Reiter - 1992 - Artificial Intelligence 56 (2-3):197-222.
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  • Approximating probabilistic inference in Bayesian belief networks is NP-hard.Paul Dagum & Michael Luby - 1993 - Artificial Intelligence 60 (1):141-153.
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