Abstract
In this essay I present a general characterization of qualitative probability, defining the concept of a qualitative probability language and proposing some bases for comparison. In particular, enumerating some of the distinctions that can be supported by a qualitative probability language induces a partial taxonomy of possible approaches. I discuss some of these in further depth, identify central issues, and suggest some general comparisons.
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References
Bacchus, F. (1989). A modest, but semantically well founded, inheritance reasoner. Eleventh Int'l Joint Conference on Artificial Intelligence, Detroit, MI, Morgan Kaufmann.
Darwiche, A. Y. (1993). A Symbolic Generalization of Probability Theory. PhD Thesis, Stanford University.
Druzdzel, M. J., and M. Henrion (1993). Efficient Reasoning in qualitative probabilistic networks. Proceedings of the Eleventh National Conference on Artificial Intelligence, Washington, DC, AAAI Press.
Dubois, D., H. Prade, L. Godo, et al. (1992). A symbolic approach to reasoning with linguistic quantifiers. Eighth Conference on Uncertainty in Artificial Intelligence, Palo Alto, CA, Morgan Kaufmann.
Gärdenfors, P. (1975). Qualitative probability as an intensional logic. Journal of Philosophical Logic 4: 171–185.
Geiger, D., T. Verma, and J. Pearl (1990). d-separation: From theorems to algorithms. Uncertainty in Artificial Intelligence 5 Ed. M. Henrion et al. North-Holland.
Goldszmidt, M., and J. Pearl (1992). Reasoning with qualitative probabilities can be tractable. Eighth Conference on Uncertainty in Artificial Intelligence, Palo Alto, CA, Morgan Kaufmann.
Goldszmidt, M. (1993). Research issues in qualitative and abstract probability. AI Magazine 15(4): 63–66.
Grosof, B. N. (1988). Non-monotonicity in probabilistic reasoning. Uncertainty in Artificial Intelligence 2 Ed. J. F. Lemmer, and L. N. Kanal. North-Holland. 237–249.
Koopman, B. O. (1940). The axioms and algebra of intuitive probability. Annals of Mathematics 42: 269–292.
Kyburg, Jr., H. E. (1994). Believing on the basis of the evidence. Computational Intelligence 10(1).
Neufeld, E. (1989). Defaults and probabilities; Extensions and coherence. First Int'l Conf. on Principles of Knowledge Representation and Reasoning, Toronto, Morgan Kaufmann.
Parsons, S. D. (1993). Qualitative Methods for Reasoning under Uncertainty. PhD Thesis, Queen Mary and Westfield College.
Pearl, J. (1988). Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. San Mateo, CA, Morgan Kaufmann.
Pearl, J., D. Geiger, and T. Verma (1989). Conditional independence and its representations. Kybernetika 25: 33–44.
Quinlan, J. R. (1983). Inferno: A cautious approach to uncertain inference. Computer Journal 26: 255–269.
Savage, L. J. (1972). The Foundations of Statistics. New York, Dover Publications.
Shachter, R. D. (1988). Probabilistic inference and influence diagrams. Operations Research 36: 589–604.
Suppes, P. (1970). A Probabilistic Theory of Causality. Amsterdam, North-Holland.
Weld, D. S., and J. de Kleer, Ed. (1989). Readings in Qualitative Reasoning About Physical Systems. Morgan Kaufmann.
Wellman, M. P. (1990). Formulation of Tradeoffs in Planning Under Uncertainty. London, Pitman.
Wellman, M. P. (1990). Fundamental Concepts of Qualitative Probabilistic Networks. Artificial Intelligence 44: 257–303.
Wellman, M. P., and M. Henrion (1993). Explaining “explaining away”. IEEE Transactions on Pattern Analysis and Machine Intelligence 15: 287–292.
Xiang, Y., M. P. Beddoes, and D. Poole (1990). Can uncertainty management be realized in a finite totally ordered probability algebra? Uncertainty in Artificial Intelligence 5 Ed. M. Henrion et al. North-Holland. 41–57.
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© 1995 Springer-Verlag Berlin Heidelberg
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Wellman, M.P. (1995). Some varieties of qualitative probability. In: Bouchon-Meunier, B., Yager, R.R., Zadeh, L.A. (eds) Advances in Intelligent Computing — IPMU '94. IPMU 1994. Lecture Notes in Computer Science, vol 945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035948
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DOI: https://doi.org/10.1007/BFb0035948
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