ProLogICA: a practical system for Abductive Logic Programming

This paper presents a new system called ProLogICA for Abductive Logic Programming (ALP) with Negation as Failure (NAF) and Integrity Constraints (ICs). The system builds upon existing ALP techniques but includes several optimisations and extensions necessitated by recent applications in computational biology, temporal reasoning and machine learning. Unlike some other ALP systems that support non-ground abduction through the integrated use of constraint solving, we adopt a more lightweight approach which avoids this complexity at the expense of only computing ground hypotheses. We argue our approach is suited to a wide class of real-world problems and demonstrate the effectiveness of \ProLogICA\ on three non-trivial applications.