Abstract
We propose an approach for modularizing P-log programs and corresponding compositional semantics based on conditional probability measures. We do so by resorting to Oikarinen and Janhunen’s definition of a logic program module and extending it to P-log by introducing the notions of input random attributes and output literals. For answering to P-log queries our method does not imply calculating all the stable models (possible worlds) of a given program, and previous calculations can be reused. Our proposal also handles probabilistic evidence by conditioning (observations).
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Viegas Damásio, C., Moura, J. (2011). Modularity of P-Log Programs. In: Delgrande, J.P., Faber, W. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2011. Lecture Notes in Computer Science(), vol 6645. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20895-9_4
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DOI: https://doi.org/10.1007/978-3-642-20895-9_4
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