Probabilistic Abductive Logic Programming in Constraint Handling Rules

A class of Probabilistic Abductive Logic Programs (PALPs) is introduced
and an implementation is developed in CHR for solving
abductive problems, providing minimal explanations with their
probabilities.
Both all-explanations and most-probable-explanations versions are given.
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Compared with other probabilistic versions of
abductive logic programming, the approach is characterized by
higher generality and a flexible and adaptable
architecture which incorporates integrity constraints and interaction
with external constraint solvers.
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A PALP is translated in a systematic way into a CHR program which serves
as a query interpreter, and the resulting CHR code describes in a highly
concise way, the strategies applied in the search for explanations.