Abseher, M., Bliem, B., Charwat, G., Dusberger, F., & Woltran, S. (2020). Computing Secure Sets in Graphs using Answer Set Programming. Journal of Logic and Computation, 30(4), 837–862. https://doi.org/10.1093/logcom/exv060 ( reposiTUm)

Abseher, M., Hecher, M., Moldovan, M., Woltran, S., & Bliem, B. (2018). Dynamic Programming on Tree Decompositions with {D-FLAT}. Kuenstliche Intelligenz, 32(2–3), 191–192. https://doi.org/10.1007/s13218-018-0531-2 ( reposiTUm)

Bliem, B., & Woltran, S. (2018). Complexity of Secure Sets. Algorithmica, 80(10), 2909–2940. https://doi.org/10.1007/s00453-017-0358-5 ( reposiTUm)

Bliem, B., & Woltran, S. (2018). Equivalence between answer-set programs under (partially) fixed input. Annals of Mathematics and Artificial Intelligence, 83(3–4), 277–295. https://doi.org/10.1007/s10472-017-9567-5 ( reposiTUm)

Bliem, B., & Woltran, S. (2018). Defensive alliances in graphs of bounded treewidth. Discrete Applied Mathematics, 251, 334–339. https://doi.org/10.1016/j.dam.2018.04.001 ( reposiTUm)

Bliem, B., Pichler, R., & Woltran, S. (2017). Implementing Courcelle’s Theorem in a declarative framework for dynamic programming. Journal of Logic and Computation, exv089. https://doi.org/10.1093/logcom/exv089 ( reposiTUm)

Abseher, M., Musliu, N., & Woltran, S. (2017). Improving the Efficiency of Dynamic Programming on Tree Decompositions via Machine Learning. Journal of Artificial Intelligence Research, 58, 829–858. https://doi.org/10.1613/jair.5312 ( reposiTUm)

Bliem, B., Charwat, G., Hecher, M., & Woltran, S. (2016). D-FLAT^2: Subset Minimization in Dynamic Programming on Tree Decompositions Made Easy. Fundamenta Informaticae, 147(1), 27–61. http://hdl.handle.net/20.500.12708/149519 ( reposiTUm)

Abseher, M., Gebser, M., Musliu, N., Schaub, T., & Woltran, S. (2016). Shift Design with Answer Set Programming. Fundamenta Informaticae, 147(1), 1–25. http://hdl.handle.net/20.500.12708/149520 ( reposiTUm)

BICHLER, M., MORAK, M., & WOLTRAN, S. (2016). The Power of Non-Ground Rules in Answer Set Programming. Theory and Practice of Logic Programming, 16(5–6), 552–569. https://doi.org/10.1017/s1471068416000338 ( reposiTUm)

Charwat, G., Dvořák, W., Gaggl, S. A., Wallner, J. P., & Woltran, S. (2015). Methods for solving reasoning problems in abstract argumentation - A survey. Artificial Intelligence, 220, 28–63. https://doi.org/10.1016/j.artint.2014.11.008 ( reposiTUm)

BLIEM, B., MORAK, M., & WOLTRAN, S. (2012). D-FLAT: Declarative Problem Solving Using Tree Decompositions and Answer-Set Programming. Theory and Practice of Logic Programming, 12(4–5), 445–464. https://doi.org/10.1017/s1471068412000129 ( reposiTUm)

Bliem, B., Moldovan, M., Morak, M., & Woltran, S. (2017). The Impact of Treewidth on ASP Grounding and Solving. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence. 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, Australia. AAAI Press. https://doi.org/10.24963/ijcai.2017/118 ( reposiTUm)

Abseher, M., Musliu, N., & Woltran, S. (2017). htd - A Free, Open-Source Framework for (Customized) Tree Decompositions and Beyond. In D. Salvagnin & M. Lombardi (Eds.), Integration of AI and OR Techniques in Constraint Programming (pp. 376–386). Lecture Notes in Computer Science / Springer. https://doi.org/10.1007/978-3-319-59776-8_30 ( reposiTUm)

Morak, M., Bichler, M., & Woltran, S. (2017). lpopt: A Rule Optimization Tool for Answer Set Programming. In M. Hermenegildo & P. Lopez-Garcia (Eds.), Logic-Based Program Synthesis and Transformation (pp. 114–130). Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-319-63139-4_7 ( reposiTUm)

Charwat, G., & Woltran, S. (2016). Dynamic Programming-based QBF Solving. In F. Lonsing & M. Seidl (Eds.), Proceedings of the 4th International Workshop on Quantified Boolean Formulas (QBF 2016) (p. 14). CEUR-WS.org. http://hdl.handle.net/20.500.12708/56683 ( reposiTUm)

Bichler, M., Morak, M., & Woltran, S. (2016). lpopt: A Rule Optimization Tool for Answer Set Programming. In M. Hermenegildo & P. Lopez-Garcia (Eds.), Pre-proceedings of the 26th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2016) (p. 14). http://hdl.handle.net/20.500.12708/56841 ( reposiTUm)

Bliem, B., Charwat, G., Hecher, M., & Woltran, S. (2016). Subset Minimization in Dynamic Programming on Tree Decompositions. In A. Darwiche (Ed.), Beyond NP, Papers from the 2016 AAAI Workshop (pp. 300–306). AAAI Press. http://hdl.handle.net/20.500.12708/56613 ( reposiTUm)

Bliem, B., Kaufmann, B., Schaub, T., & Woltran, S. (2016). ASP for Anytime Dynamic Programming on Tree Decompositions. In S. Kambhampati (Ed.), Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9-15 July 2016 (pp. 979–986). IJCAI/AAAI Press. http://hdl.handle.net/20.500.12708/56682 ( reposiTUm)

Bliem, B., Hecher, M., & Woltran, S. (2016). On Efficiently Enumerating Semi-Stable Extensions via Dynamic Programming on Tree Decompositions. In P. Baroni, T. F. Gordon, T. Scheffler, & M. Stede (Eds.), Computational Models of Argument (pp. 107–118). IOS Press. http://hdl.handle.net/20.500.12708/56690 ( reposiTUm)

Bliem, B., Kaufmann, B., Schaub, T., & Woltran, S. (2016). ASP for Anytime Dynamic Programming on Tree Decompositions (Extended Abstract). In G. Friedrich, M. Helmert, & F. Wotawa (Eds.), KI 2016: Advances in Artificial Intelligence (pp. 257–263). LNCS/Springer. http://hdl.handle.net/20.500.12708/56694 ( reposiTUm)

Bliem, B., & Woltran, S. (2016). Complexity of Secure Sets. In E. W. Mayr (Ed.), Graph-Theoretic Concepts in Computer Science (pp. 64–77). LNCS/Springer. https://doi.org/10.1007/978-3-662-53174-7_5 ( reposiTUm)

Abseher, M., Moldovan, M., & Woltran, S. (2016). Providing Built-In Counters in a Declarative Dynamic Programming Environment. In G. Friedrich, M. Helmert, & F. Wotawa (Eds.), KI 2016: Advances in Artificial Intelligence (pp. 3–16). LNCS/Springer. https://doi.org/10.1007/978-3-319-46073-4_1 ( reposiTUm)

Bliem, B., & Woltran, S. (2016). Equivalence Between Answer-Set Programs Under (Partially) Fixed Input. In M. Gyssens & G. R. Simari (Eds.), Foundations of Information and Knowledge Systems : 9th International Symposium, FoIKS 2016, Linz, Austria, March 7-11, 2016. Proceedings (pp. 95–111). Lecture Notes in Computer Science (LNCS) / Springer. https://doi.org/10.1007/978-3-319-30024-5_6 ( reposiTUm)

Bliem, B., Charwat, G., Hecher, M., & Woltran, S. (2015). D-FLAT^2: Subset Minimization in Dynamic Programming on Tree Decompositions Made Easy. In D. Inclezan & M. Maratea (Eds.), 8th Workshop on Answer Set Programming and Other Computing Paradigms, ASPOCP 2015 (p. 15). http://hdl.handle.net/20.500.12708/56186 ( reposiTUm)

Abseher, M., Gebser, M., Musliu, N., Schaub, T., & Woltran, S. (2015). Shift Design with Answer Set Programming. In D. Inclezan & M. Maratea (Eds.), 8th Workshop on Answer Set Programming and Other Computing Paradigms, ASPOCP 2015 (p. 13). http://hdl.handle.net/20.500.12708/56218 ( reposiTUm)

Dusberger, F., Abseher, M., Musliu, N., & Woltran, S. (2015). Improving the Efficiency of Dynamic Programming on Tree Decompositions via Machine Learning. In Q. Yang & M. Wooldridge (Eds.), Proceedings of IJCAI 2015, the 24th International Joint Conference on Artificial Intelligence (pp. 275–282). AAAI Press. http://hdl.handle.net/20.500.12708/56206 ( reposiTUm)

Charwat, G., & Woltran, S. (2015). Efficient Problem Solving on Tree Decompositions Using Binary Decision Diagrams. In F. Calimeri, G. Ianni, & M. Truszczynski (Eds.), Logic Programming and Nonmonotonic Reasoning (pp. 213–227). Springer. https://doi.org/10.1007/978-3-319-23264-5_19 ( reposiTUm)

Charwat, G., & Pfandler, A. (2015). Democratix: A Declarative Approach to Winner Determination. In T. Walsh (Ed.), Algorithmic Decision Theory (pp. 253–269). Springer. https://doi.org/10.1007/978-3-319-23114-3_16 ( reposiTUm)

Abseher, M., Gebser, M., Musliu, N., Schaub, T., & Woltran, S. (2015). Shift Design with Answer Set Programming. In F. Calimeri, G. Ianni, & M. Truszczynski (Eds.), Logic Programming and Nonmonotonic Reasoning (pp. 32–39). Springer. https://doi.org/10.1007/978-3-319-23264-5_4 ( reposiTUm)

Abseher, M., Bliem, B., Charwat, G., Dusberger, F., & Woltran, S. (2014). Computing Secure Sets in Graphs using Answer Set Programming. In 7th Workshop on Answer Set Programming and Other Computing Paradigms, ASPOCP 2014. ASPOCP 2014 - 7th Workshop on Answer Set Programming and Other Computing Paradigms, Wien, Austria. http://hdl.handle.net/20.500.12708/55222 ( reposiTUm)

Charwat, G., & Pfandler, A. (2014). DEMOCRATIX: A Declarative Approach to Winner Determination. In A. Procaccia & T. Walsh (Eds.), Proceedings of the Fifth International Workshop on Computational Social Choice (p. 15). http://hdl.handle.net/20.500.12708/55772 ( reposiTUm)

Abseher, M., Bliem, B., Charwat, G., Dusberger, F., Hecher, M., & Woltran, S. (2014). The D-FLAT System for Dynamic Programming on Tree Decompositions. In E. Fermé & J. Leite (Eds.), Logics in Artificial Intelligence (pp. 558–572). Springer. https://doi.org/10.1007/978-3-319-11558-0_39 ( reposiTUm)

Bliem, B., Pichler, R., & Woltran, S. (2013). Declarative Dynamic Programming as an Alternative Realization of Courcelle’s Theorem. In G. Gutin & S. Szeider (Eds.), Parameterized and Exact Computation (pp. 28–40). Springer. https://doi.org/10.1007/978-3-319-03898-8_4 ( reposiTUm)

Bliem, B., Pichler, R., & Woltran, S. (2013). Applicability of ASP-based Problem Solving on Tree Decompositions. Third International Workshop on Graph Structures for Knowledge Representation and Reasoning (GKR) 2013, Peking, China. http://hdl.handle.net/20.500.12708/85667 ( reposiTUm)

Bliem, B., Charwat, G., Hecher, M., & Woltran, S. (2015). D-FLAT^2: Subset Minimization in Dynamic Programming on Tree Decompositions Made Easy (DBAI-TR-2015-93). http://hdl.handle.net/20.500.12708/38634 ( reposiTUm)

Abseher, M., Bliem, B., Charwat, G., Dusberger, F., Hecher, M., & Woltran, S. (2014). D-FLAT: Progress Report (DBAI-TR-2014-86). http://hdl.handle.net/20.500.12708/38156 ( reposiTUm)