@article{3988,
  author = {Domenico Corapi, Alessandra Russo and Emil Lupu},
  title = {Implementation of Top-Direct Abductive Learning based on Mapping ILP Approach},
  journal = {Journal of Data Processing},
  year = {2024},
  volume = {14},
  number = {1},
  doi = {https://doi.org/10.6025/jdp/2024/14/1/11-20},
  url = {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. Tal’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.},
}