| Saarplan: Combining saarland’s greatest planning techniques M Fickert, D Gnad, P Speicher, J Hoffmann IPC2018–Classical Tracks, 10-15, 2018 | 21 | 2018 |
| Combining the delete relaxation with critical-path heuristics: A direct characterization M Fickert, J Hoffmann, M Steinmetz Journal of Artificial Intelligence Research 56, 269-327, 2016 | 17 | 2016 |
| Complete local search: Boosting hill-climbing through online relaxation refinement M Fickert, J Hoffmann Proceedings of the International Conference on Automated Planning and …, 2017 | 15 | 2017 |
| Explicit Conjunctions without Compilation: Computing hFF (PiC) in Polynomial Time J Hoffmann, M Fickert Proceedings of the International Conference on Automated Planning and …, 2015 | 14 | 2015 |
| A novel dual ascent algorithm for solving the min-cost flow problem R Becker, M Fickert, A Karrenbauer 2016 Proceedings of the Eighteenth Workshop on Algorithm Engineering and …, 2016 | 13 | 2016 |
| OLCFF: Online-learning hCFF M Fickert, J Hoffmann Ninth International Planning Competition (IPC-9): Planner Abstracts, 17-19, 2018 | 12 | 2018 |
| A novel lookahead strategy for delete relaxation heuristics in greedy best-first search M Fickert Proceedings of the International Conference on Automated Planning and …, 2020 | 10 | 2020 |
| Making hill-climbing great again through online relaxation refinement and novelty pruning M Fickert Proceedings of the International Symposium on Combinatorial Search 9 (1 …, 2018 | 9 | 2018 |
| New Results in Bounded-Suboptimal Search M Fickert, T Gu, W Ruml Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 10166 …, 2022 | 7 | 2022 |
| Beliefs we can believe in: Replacing assumptions with data in real-time search M Fickert, T Gu, L Staut, W Ruml, J Hoffmann, M Petrik Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 9827-9834, 2020 | 7 | 2020 |
| Online refinement of Cartesian abstraction heuristics R Eifler, M Fickert Proceedings of the International Symposium on Combinatorial Search 9 (1), 46-54, 2018 | 7 | 2018 |
| Ranking conjunctions for partial delete relaxation heuristics in planning M Fickert, J Hoffmann Proceedings of the International Symposium on Combinatorial Search 8 (1), 38-46, 2017 | 7 | 2017 |
| Choosing the Initial State for Online Replanning M Fickert, I Gavran, I Fedotov, J Hoffmann, R Majumdar, W Ruml Proceedings of the AAAI Conference on Artificial Intelligence 35 (14), 12311 …, 2021 | 3 | 2021 |
| Bounded-cost search using estimates of uncertainty M Fickert, T Gu, W Ruml Proceedings of IJCAI-21, 2021 | 3 | 2021 |
| Novel is not always better: On the relation between novelty and dominance pruning J Groß, A Torralba, M Fickert Proceedings of the AAAI Conference on Artificial Intelligence 34 (06), 9875-9882, 2020 | 3 | 2020 |
| Refining abstraction heuristics during real-time planning R Eifler, M Fickert, J Hoffmann, W Ruml Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7578-7585, 2019 | 3 | 2019 |
| DiSCO: Decoupled Search+ COnjunctions M Fickert, D Gnad en. In, 58-60, 2023 | 2 | 2023 |
| Online Relaxation Refinement for Satisficing Planning: On Partial Delete Relaxation, Complete Hill-Climbing, and Novelty Pruning M Fickert, J Hoffmann Journal of Artificial Intelligence Research 73, 67–115, 2022 | 2 | 2022 |
| Real-time planning as data-driven decision-making M Fickert, T Gu, L Staut, S Lekyang, W Ruml, J Hoffmann, M Petrik the ICAPS-20 Workshop on Bridging the Gap Between AI Planning and …, 2020 | 2 | 2020 |
| Unchaining the Power of Partial Delete Relaxation, Part II: Finding Plans with Red-Black State Space Search. M Fickert, D Gnad, J Hoffmann IJCAI, 4750-4756, 2018 | 2 | 2018 |
