| Adapting novelty to classical planning as heuristic search M Katz, N Lipovetzky, D Moshkovich, A Tuisov Proceedings of the International Conference on Automated Planning and …, 2017 | 39 | 2017 |
| Blind search for atarilike online planning revisited A Shleyfman, A Tuisov, C Domshlak Heuristics and Search for Domain-independent Planning (HSDIP), 85, 2016 | 34 | 2016 |
| Merwin planner: Mercury enchanced with novelty heuristic M Katz, N Lipovetzky, D Moshkovich, A Tuisov IPC 2018 planner abstracts, 53-56, 2018 | 16 | 2018 |
| The Fewer the Merrier: Pruning Preferred Operators with Novelty A Tuisov, M Katz IJCAI 2021, 2021 | 5 | 2021 |
| The continuous joint replenishment problem is strongly NP-hard A Tuisov, L Yedidsion arXiv preprint arXiv:2006.05310, 2020 | 5 | 2020 |
| Automated Verification of Social Law Robustness for Reactive Agents A Tuisov, E Karpas ECAI 2020, 2386-2393, 2020 | 3 | 2020 |
| Artificial intelligence automated planning based on biomedical parameters M Katz, D Moshkovich, A Tuisov US Patent App. 16/144,028, 2020 | 2 | 2020 |
| LLM-Generated Heuristics for AI Planning: Do We Even Need Domain-Independence Anymore? A Tuisov, Y Vernik, A Shleyfman arXiv preprint arXiv:2501.18784, 2025 | 1 | 2025 |
| Good Things Come to Those Who Wait: The Power of Sensing in Social Laws A Tuisov, A Shleyfman, E Karpas | 1 | 2024 |
| TFTM-ArgMax Planner: Pruning Preferred Operators with Novelty M Katz, A Tuisov en. In, 58-60, 2023 | 1 | 2023 |
| TFTM-CO1 Planner: Pruning Preferred Operators with Novelty M Katz, A Tuisov | | 2023 |
| OSOUM Framework for Trading Data Research G Goren, R Shraga, A Tuisov arXiv preprint arXiv:2103.01778, 2021 | | 2021 |
| Application of MCTS in Atari Black-box Planning A Shleyfman, A Tuisov, C Domshlak HSDIP 2018, 59, 2018 | | 2018 |
Michael KatzPrincipal Research Staff Member, IBM Research AIE-mail megerősítve itt: ibm.com