Kaminski, R., Schaub, T., Strauch, K., & Svancara Jirı́. (2024). Improving the Sum-of-Cost Methods for Reduction-Based Multi-Agent Pathfinding Solvers. In ICAART (1) (pp. 264–271). SCITEPRESS.[bib]
Svancara Jirı́, Atzmon, D., Strauch, K., Kaminski, R., & Schaub, T. (2024). Which Objective Function is Solved Faster in Multi-Agent Pathfinding? It Depends. In ICAART (3) (pp. 23–33). SCITEPRESS.[bib]
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]
2022
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]