Abstract
Most techniques for probabilistic reasoning focus on reasoning about conditional probability constraints. However, human experts are accustomed to representing uncertain knowledge in the form of expectation rather than probability distribution directly in many cases. It is necessary to provide a logic for encoding hybrid probabilistic knowledge bases that contain expectation knowledge as well as the purely probabilistic knowledge in the form of conditional probability. This paper constructs a nonmonotonic logic for reasoning about hybrid probabilistic knowledge bases. We extend the propositional logic for reasoning about expectation to encoding hybrid probabilistic knowledge by introducing the conditional expectation constraint formula. Then we provide an approach to nonmonotonic reasoning about hybrid probabilistic knowledge bases. Finally,we compare this logic with related works.
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© 2006 Springer-Verlag Berlin Heidelberg
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Mu, K., Lin, Z., Jin, Z., Lu, R. (2006). Reasoning About Hybrid Probabilistic Knowledge Bases. In: Yang, Q., Webb, G. (eds) PRICAI 2006: Trends in Artificial Intelligence. PRICAI 2006. Lecture Notes in Computer Science(), vol 4099. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36668-3_16
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DOI: https://doi.org/10.1007/978-3-540-36668-3_16
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