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<p>An approach to nonmonotonic reasoning that combines the principle of infinitesimal probabilities with that of maximum entropy, thus extending the inferential power of the probabilistic interpretation of defaults, is proposed. A precise formalization of the consequences entailed by a conditional knowledge base is provided, the computational machinery necessary for drawing these consequences is developed, and the behavior of the maximum entropy approach is compared to related work in default reasoning. The resulting formalism offers a compromise between two extremes: the cautious approach based on the conditional interpretations of defaults and the bold approach based on minimizing abnormalities.</p>
abnormality minimisation; inference; maximum entropy; nonmonotonic reasoning; infinitesimal probabilities; probabilistic interpretation; conditional knowledge base; conditional interpretations; knowledge based systems; nonmonotonic reasoning; probabilistic logic

J. Pearl, M. Goldzsmidt and P. Morris, "A Maximum Entropy Approach to Nonmonotonic Reasoning," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 15, no. , pp. 220-232, 1993.
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