Research Papers


ILASP has been developed as part of a comprehensive package of research on the theory and practice of learning ASP programs. Mark Law's PhD thesis presents each of the ILASP algorithms in detail, along with theoretical results on learning ASP programs. Parts of the work in the thesis led to several conference and journal publications.

Thesis


[1 Mark Law. Inductive learning of answer set programs. Imperial College London, 2018. [  pdf  ]


Selected Publications


[1 Mark Law, Alessandra Russo, and Krysia Broda. Inductive learning of answer set programs. In Logics in Artificial Intelligence - 14th European Conference, JELIA 2014, Funchal, Madeira, Portugal, September 24-26, 2014. Proceedings, pages 311-325, 2014. [  paper | pdf | proofs  ]

[2 Mark Law, Alessandra Russo, and Krysia Broda. Learning Weak Constraints in Answer Set Programming. In Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 15, 2015. [  pdf | proofs  ]

[3 Mark Law, Alessandra Russo, and Krysia Broda. Iterative Learning of Answer Set Programs from Context Dependent Examples. In Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 16, 2016. [  pdf  ]

[4 Mark Law, Alessandra Russo, and Krysia Broda. The complexity and generality of learning answer set programs. Artificial Intelligence, 2018. [  pdf  ]

[5 Mark Law, Alessandra Russo, and Krysia Broda. Inductive Learning of Answer Set Programs from Noisy Examples. To appear in Advances in Cognitive Systems, 2018. [  pdf  ]