Knowledge Processing and Information Systems
Javier Romero Davila

M.S. Javier Romero Davila

University of Potsdam
Institute of Computer Science
An der Bahn 2
D-14476 Potsdam

Campus Golm, Building 70, Room 02.29

Phone   +49-331-977-3092
Email  javier@cs.uni-potsdam.de

Publications

2024

  1. Romero, J., Schaub, T., & Strauch, K. (2024). On the generalization of learned constraints for ASP solving in temporal domains. CoRR, abs/2401.16124. [pdf] [bib]

2023

  1. Fandinno, J., Mishra, S., Romero, J., & Schaub, T. (2023). Answer Set Programming Made Easy. In Analysis, Verification and Transformation for Declarative Programming and Intelligent Systems (Vol. 13160, pp. 133–150). Springer. [pdf] [bib]
  2. Hahn, S., Martens, C., Nemes, A., Otunuya, H., Romero, J., Schaub, T., & Schellhorn, S. (2023). Reasoning about Study Regulations in Answer Set Programming (Preliminary Report). In ICLP Workshops (Vol. 3437). CEUR-WS.org. [pdf] [bib]
  3. Brewka, G., Delgrande, J. P., Romero, J., & Schaub, T. (2023). A general framework for preferences in answer set programming. Artif. Intell., 325, 104023. [pdf] [bib]
  4. Kaminski, R., Romero, J., Schaub, T., & Wanko, P. (2023). How to Build Your Own ASP-based System?! Theory Pract. Log. Program., 23(1), 299–361. [pdf] [bib]

2022

  1. Romero, J., Schaub, T., & Strauch, K. (2022). On the Generalization of Learned Constraints for ASP Solving in Temporal Domains. In RuleML+RR (Vol. 13752, pp. 20–37). Springer. [bib]
  2. Hahn, S., Janhunen, T., Kaminski, R., Romero, J., Rühling, N., & Schaub, T. (2022). Plingo: A System for Probabilistic Reasoning in Clingo Based on LP^MLN. In RuleML+RR (Vol. 13752, pp. 54–62). Springer. [pdf] [bib]
  3. Hahn, S., Janhunen, T., Kaminski, R., Romero, J., Rühling, N., & Schaub, T. (2022). plingo: A system for probabilistic reasoning in clingo based on lpmln. CoRR, abs/2206.11515. [pdf] [bib]

2021

  1. Rodriguez, I. D., Bonet, B., Romero, J., & Geffner, H. (2021). Learning First-Order Representations for Planning from Black Box States: New Results. In KR (pp. 539–548). [pdf] [bib]
  2. Rodriguez, I. D., Bonet, B., Romero, J., & Geffner, H. (2021). Learning First-Order Representations for Planning from Black-Box States: New Results. CoRR, abs/2105.10830. [pdf] [bib]
  3. Fandinno, J., Laferrière, F., Romero, J., Schaub, T., & Son, T. C. (2021). Planning with Incomplete Information in Quantified Answer Set Programming. CoRR, abs/2108.06405. [pdf] [bib]
  4. Fandinno, J., Mishra, S., Romero, J., & Schaub, T. (2021). Answer Set Programming Made Easy. CoRR, abs/2111.06366. [pdf] [bib]
  5. Fandinno, J., Laferrière, F., Romero, J., Schaub, T., & Son, T. C. (2021). Planning with Incomplete Information in Quantified Answer Set Programming. Theory Pract. Log. Program., 21(5), 663–679. [pdf] [bib]

2020

  1. Cabalar, P., Fandinno, J., Garea, J., Romero, J., & Schaub, T. (2020). eclingo: A solver for Epistemic Logic Programs. CoRR, abs/2008.02018. [pdf] [bib]
  2. Kaminski, R., Romero, J., Schaub, T., & Wanko, P. (2020). How to build your own ASP-based system?! CoRR, abs/2008.06692. [pdf] [bib]
  3. Cabalar, P., Fandinno, J., Garea, J., Romero, J., & Schaub, T. (2020). eclingo : A Solver for Epistemic Logic Programs. Theory Pract. Log. Program., 20(6), 834–847. [pdf] [bib]
  4. Fandinno, J., Mishra, S., Romero, J., & Schaub, T. (2020). Answer Set Programming Made Easy. In ASPOCP@ICLP. [pdf] [bib]

2019

  1. Alviano, M., Romero, J., & Schaub, T. (2019). On the Integration of CP-nets in ASPRIN. In IJCAI (pp. 1495–1501). ijcai.org. [pdf] [bib]
  2. Obermeier, P., Romero, J., & Schaub, T. (2019). Multi-Shot Stream Reasoning in Answer Set Programming: A Preliminary Report. OJDB, 6(1), 33–38. [pdf] [bib]
  3. Dimopoulos, Y., Gebser, M., Lühne, P., Romero, J., & Schaub, T. (2019). plasp 3: Towards Effective ASP Planning. TPLP, 19(3), 477–504. [pdf] [bib]

2018

  1. Razzaq, M., Kaminski, R., Romero, J., Schaub, T., Bourdon, J., & Guziolowski, C. (2018). Computing Diverse Boolean Networks from Phosphoproteomic Time Series Data. In CMSB (Vol. 11095, pp. 59–74). Springer. [pdf] [bib]
  2. Alviano, M., Romero, J., & Schaub, T. (2018). Preference Relations by Approximation. In KR (pp. 2–11). AAAI Press. [pdf] [bib]
  3. Dimopoulos, Y., Gebser, M., Lühne, P., Romero, J., & Schaub, T. (2018). plasp 3: Towards Effective ASP Planning. CoRR, abs/1812.04491. [pdf] [bib]
  4. Brewka, G., Ellmauthaler, S., Kern-Isberner, G., Obermeier, P., Ostrowski, M., Romero, J., … Schieweck, S. (2018). Advanced Solving Technology for Dynamic and Reactive Applications. KI, 32(2-3), 199–200. [pdf] [bib]
  5. Gebser, M., Kaminski, R., Kaufmann, B., Lühne, P., Obermeier, P., Ostrowski, M., … Wanko, P. (2018). The Potsdam Answer Set Solving Collection 5.0. KI, 32(2-3), 181–182. [pdf] [bib]

2017

  1. Romero, J., Schaub, T., & Son, T. C. (2017). Generalized Answer Set Planning with Incomplete Information. In ASPOCP@LPNMR (Vol. 1868). CEUR-WS.org. [pdf] [bib]
  2. Dimopoulos, Y., Gebser, M., Lühne, P., Romero, J., & Schaub, T. (2017). plasp 3: Towards Effective ASP Planning. In LPNMR (Vol. 10377, pp. 286–300). Springer. [pdf] [bib]
  3. Romero, J. (2017). asprin: Answer Set Programming with Preferences. In BTW (pp. 159–162). Bonn: Gesellschaft für Informatik e.V. [pdf] [bib]
  4. Romero, J. (2017). Extending Answer Set Programming with Declarative Heuristics, Preferences, and Online Planning. In DC@LPNMR (pp. 28–30). [pdf] [bib]

2016

  1. Romero, J., Schaub, T., & Wanko, P. (2016). Computing Diverse Optimal Stable Models. In ICLP (Technical Communications) (Vol. 52, pp. 3:1–3:14). Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik. [pdf] [bib]
  2. Gebser, M., Kaminski, R., Kaufmann, B., Lühne, P., Romero, J., & Schaub, T. (2016). Answer Set Solving with Generalized Learned Constraints. In ICLP (Technical Communications) (Vol. 52, pp. 9:1–9:15). Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik. [pdf] [bib]
  3. Gebser, M., Guyet, T., Quiniou, R., Romero, J., & Schaub, T. (2016). Knowledge-Based Sequence Mining with ASP. In IJCAI (pp. 1497–1504). IJCAI/AAAI Press. [pdf] [bib]

2015

  1. Brewka, G., Delgrande, J. P., Romero, J., & Schaub, T. (2015). asprin: Customizing Answer Set Preferences without a Headache. In AAAI (pp. 1467–1474). AAAI Press. [pdf] [bib]
  2. Andres, B., Biewer, A., Romero, J., Haubelt, C., & Schaub, T. (2015). Improving Coordinated SMT-Based System Synthesis by Utilizing Domain-Specific Heuristics. In LPNMR (Vol. 9345, pp. 55–68). Springer. [pdf] [bib]
  3. Brewka, G., Delgrande, J. P., Romero, J., & Schaub, T. (2015). Implementing Preferences with asprin. In LPNMR (Vol. 9345, pp. 158–172). Springer. [pdf] [bib]
  4. Gebser, M., Kaminski, R., Kaufmann, B., Romero, J., & Schaub, T. (2015). Progress in clasp Series 3. In LPNMR (Vol. 9345, pp. 368–383). Springer. [pdf] [bib]

2014

  1. Brewka, G., Delgrande, J. P., Romero, J., & Schaub, T. (2014). Are Preferences Giving You a Headache? — Take asprin! In ASPOCP@LPNMR. [pdf] [bib]

2013

  1. Gebser, M., Kaufmann, B., Romero, J., Otero, R., Schaub, T., & Wanko, P. (2013). Domain-Specific Heuristics in Answer Set Programming. In AAAI. AAAI Press. [pdf] [bib]