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  1. The computational complexity of probabilistic inference using bayesian belief networks.Gregory F. Cooper - 1990 - Artificial Intelligence 42 (2-3):393-405.
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  • Heuristic classification.William J. Clancey - 1985 - Artificial Intelligence 27 (3):289-350.
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  • Commonsense reasoning about causality: Deriving behavior from structure.Benjamin Kuipers - 1984 - Artificial Intelligence 24 (1-3):169-203.
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  • The ethical decision-making processes of information systems workers.David B. Paradice & Roy M. Dejoie - 1991 - Journal of Business Ethics 10 (1):1 - 21.
    An empirical investigation was conducted to determine whether management information systems (MIS) majors, on average, exhibit ethical decision-making processes that differ from students in other functional business areas. The research also examined whether the existence of a computer-based information system in an ethical dilemma influences ethical desision-making processes. Although student subjects were used, the research instrument has been highly correlated with educational levels attained by adult subjects in similar studies. Thus, we feel that our results have a high likelihood of (...)
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  • Nonmonotonic Reasoning and Causation.Yoav Shoham - 1990 - Cognitive Science 14 (2):213-252.
    It is suggested that taking into account considerations that traditionally fall within the scope of computer science in general, and artificial intelligence in particular, sheds new light on the subject of causation. It is argued that adopting causal notions con be viewed as filling a computational need: They allow reasoning with incomplete information, facilitate economical representations, and afford relatively efficient methods for reasoning about those representations. Specifically, it is proposed that causal reasoning is intimately bound to nonmonotonic reasoning. An account (...)
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  • XPLAIN: a system for creating and explaining expert consulting programs.William R. Swartout - 1983 - Artificial Intelligence 21 (3):285-325.
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  • Causal approximations.P. Pandurang Nayak - 1994 - Artificial Intelligence 70 (1-2):277-334.
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  • Concept learning and heuristic classification in weak-theory domains.Bruce W. Porter, Ray Bareiss & Robert C. Holte - 1990 - Artificial Intelligence 45 (1-2):229-263.
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  • Fundamental concepts of qualitative probabilistic networks.Michael P. Wellman - 1990 - Artificial Intelligence 44 (3):257-303.
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  • Analysis of notions of diagnosis.Peter J. F. Lucas - 1998 - Artificial Intelligence 105 (1-2):295-343.
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  • Using empirical analysis to refine expert system knowledge bases.Peter Politakis & Sholom M. Weiss - 1984 - Artificial Intelligence 22 (1):23-48.
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  • The roles of associational and causal reasoning in problem solving.Reid G. Simmons - 1992 - Artificial Intelligence 53 (2-3):159-207.
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  • Qualitative superposition.Enrico W. Coiera - 1992 - Artificial Intelligence 56 (2-3):171-196.
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  • (1 other version)Three paradoxes of medical diagnosis.G. William Moore & Grover M. Hutchins - 1981 - Metamedicine 2 (2):197-215.
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  • (1 other version)Three paradoxes of medical diagnosis.G. William Moore & Grover M. Hutchins - 1987 - Theoretical Medicine and Bioethics 2 (2):197-215.
    Sadegh-zadeh [23] has proposed a theory of the relativity of medical diagnosis in terms of the time at which a diagnosis is accepted, the patient to whom the diagnosis applies, the physician who renders the diagnosis, the medical knowledge used, the diagnostic method applied, and the set of patient observations. Use of classical formal logic as the diagnostic method may result in three paradoxes: the paradoxes of consistency, completeness, and justifiable ignorance. These paradoxes may be resolved by the addition of (...)
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  • Memory‐Based Hypothesis Formation: Heuristic Learning of Commonsense Causal Relations from Text.H. Cem Bozsahin & Nicholas V. Findler - 1992 - Cognitive Science 16 (4):431-454.
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  • A method for managing evidential reasoning in a hierarchical hypothesis space: a retrospective.Jean Gordon & Edward H. Shortliffe - 1993 - Artificial Intelligence 59 (1-2):43-47.
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  • Causality as a key to the frame problem.Hideyuki Nakashima, Hitoshi Matsubara & Ichiro Osawa - 1997 - Artificial Intelligence 91 (1):33-50.
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