Abstract
Probabilistic conditionals are a powerful means for expressing uncertain knowledge. In this paper, we describe a system implemented in Java performing probabilistic reasoning at optimum entropy. It provides nonmonotonic belief change operations like revision and update and supports advanced querying facilities including diagnosis and what-if-analysis.
The research reported here was supported by the Deutsche Forschungsgemeinschaft (grants BE 1700/7-1 and KE 1413/2-1).
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Finthammer, M., Beierle, C., Berger, B., Kern-Isberner, G. (2009). An Implementation of Belief Change Operations Based on Probabilistic Conditional Logic. In: Erdem, E., Lin, F., Schaub, T. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2009. Lecture Notes in Computer Science(), vol 5753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04238-6_48
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DOI: https://doi.org/10.1007/978-3-642-04238-6_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04237-9
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