Implementation of Top-Direct Abductive Learning based on Mapping ILP Approach
Domenico Corapi, Alessandra Russo and Emil Lupu
Journal of Data Processing, Vol. 14, No. 1, 2024.
DOI: https://doi.org/10.6025/jdp/2024/14/1/11-20
Link: https://www.dline.info/jdp/fulltext/v14n1/jdpv14n1_2.pdf
Abstract:
It is introducing a new non-monotonic ILP ( NILP ) approach, and its implementation is called top-direct abductive learning (TAL). TAL addresses some shortcomings of inverse-entailed ILP systems and is the first Top-Down ILP system to allow background theories and hypotheses to be normal logic programs. Talâ€™s approach is based on mapping an ILP problem to an equivalent ALP one. This allows the use of well-established ALP proof procedures and the specification of richer language biases with integrity constraints. The mapping provides a principled search space for the ILP problem and allows an abductive search to compute inductive solutions.