Saribatur, Z. G., Eiter, T., & Schüller, P. (2021). Abstraction for non-ground answer set programs. Artificial Intelligence, 300(103563), 103563. https://doi.org/10.1016/j.artint.2021.103563 ( reposiTUm)

Mansouri, M., Pecora, F., & Schüller, P. (2021). Combining Task and Motion Planning: Challenges and Guidelines. Frontiers in Robotics and AI, 8. https://doi.org/10.3389/frobt.2021.637888 ( reposiTUm)

CUTERI, B., DODARO, C., RICCA, F., & SCHÜLLER, P. (2019). Partial Compilation of ASP Programs. Theory and Practice of Logic Programming, 19(5–6), 857–873. https://doi.org/10.1017/s1471068419000231 ( reposiTUm)

Bozzato, L., Eiter, T., Kiesel, R. P. D., & Stepanova, D. (2023). Semantically Guided Scene Generation via Contextual Reasoning and Algebraic Measures. In Proceedings of the International Conference on Logic Programming 2023 Workshops co-located with the 39th International Conference on Logic Programming (ICLP 2023). 16th Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP 2023), London, United Kingdom of Great Britain and Northern Ireland (the). CEUR-WS.org. https://doi.org/10.34726/5412 ( reposiTUm)

Schüller, P. (2020). A new OWLAPI interface for HEX-programs applied to explaining contingencies in production planning. In A. Saffiotti, L. Serafini, & P. Lukowicz (Eds.), Proceedings of the First International Workshop on New Foundations for Human-Centered AI (NeHuAI) co-located with 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostella, Spain, September 4, 2020 (p. 6). CEUR Workshop Proceedings. http://hdl.handle.net/20.500.12708/55553 ( reposiTUm)

Schüller, P. (2019). The Hexlite Solver. In Logics in Artificial Intelligence (pp. 593–607). Springer, Cham, Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-19570-0_39 ( reposiTUm)

Saribatur, Z. G., Eiter, T., & Schüller, P. (2019). Abstraction for Non-Ground Answer Set Programs (LOGCOMP RR-1923-19-01). http://hdl.handle.net/20.500.12708/39887 ( reposiTUm)

Bozzato, L., Eiter, T., Kiesel, R. P. D., & Stepanova, D. (2023). Contextual Reasoning for Scene Generation. Technical Report. arXiv. https://doi.org/10.48550/arXiv.2305.02255 ( reposiTUm)