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

2025

  1. Becker, A., Cabalar, P., Diéguez Martı́n, Romero, J., Hahn, S., & Schaub, T. (2025). Compiling Metric Temporal Answer Set Programming. CoRR, abs/2506.08150. [pdf] [bib]
  2. Hahn, S., Janhunen, T., Kaminski, R., Romero, J., Rühling, N., & Schaub, T. (2025). Plingo: A System for Probabilistic Reasoning in Answer Set Programming. Theory Pract. Log. Program., 25(2), 134–167. [bib]
  3. Romero, J., Schaub, T., & Strauch, K. (2025). On the Generalization of Learned Constraints for ASP Solving in Temporal Domains. Theory Pract. Log. Program., 25(2), 197–224. [bib]

2024

  1. Becker, A., Cabalar, P., Diéguez Martı́n, Hahn, S., Romero, J., & Schaub, T. (2024). Compiling Metric Temporal Answer Set Programming. LPNMR, 15245, 15–29. [pdf] [bib]
  2. 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]
  3. Hahn, S., Martens, C., Nemes, A., Otunuya, H., Romero, J., Schaub, T., & Schellhorn, S. (2024). Reasoning about Study Regulations in Answer Set Programming. CoRR, abs/2408.04528. [pdf] [bib]
  4. Hahn, S., Schaub, T., Martens, C., Nemes, A., Otunuya, H., Romero, J., & Schellhorn, S. (2024). Reasoning About Study Regulations in Answer Set Programming. Theory Pract. Log. Program., 24(4), 790–804. [bib]

2023

  1. Fandinno, J., Mishra, S., Romero, J., & Schaub, T. (2023). Answer Set Programming Made Easy. Analysis, Verification and Transformation for Declarative Programming and Intelligent Systems, 13160, 133–150. [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). ICLP Workshops, 3437. [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. RuleML+RR, 13752, 20–37. [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. RuleML+RR, 13752, 54–62. [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. KR, 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. ASPOCP@ICLP. [pdf] [bib]

2019

  1. Alviano, M., Romero, J., & Schaub, T. (2019). On the Integration of CP-nets in ASPRIN. IJCAI, 1495–1501. [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. CMSB, 11095, 59–74. [pdf] [bib]
  2. Alviano, M., Romero, J., & Schaub, T. (2018). Preference Relations by Approximation. KR, 2–11. [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., Schaub, T., & 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., Romero, J., Schaub, T., Schellhorn, S., & 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. ASPOCP@LPNMR, 1868. [pdf] [bib]
  2. Dimopoulos, Y., Gebser, M., Lühne, P., Romero, J., & Schaub, T. (2017). plasp 3: Towards Effective ASP Planning. LPNMR, 10377, 286–300. [pdf] [bib]
  3. Romero, J. (2017). asprin: Answer Set Programming with Preferences. BTW, 159–162. [pdf] [bib]
  4. Romero, J. (2017). Extending Answer Set Programming with Declarative Heuristics, Preferences, and Online Planning. DC@LPNMR, 28–30. [pdf] [bib]

2016

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

2015

  1. Brewka, G., Delgrande, J. P., Romero, J., & Schaub, T. (2015). asprin: Customizing Answer Set Preferences without a Headache. AAAI, 1467–1474. [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. LPNMR, 9345, 55–68. [pdf] [bib]
  3. Brewka, G., Delgrande, J. P., Romero, J., & Schaub, T. (2015). Implementing Preferences with asprin. LPNMR, 9345, 158–172. [pdf] [bib]
  4. Gebser, M., Kaminski, R., Kaufmann, B., Romero, J., & Schaub, T. (2015). Progress in clasp Series 3. LPNMR, 9345, 368–383. [pdf] [bib]

2014

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