Artykuły udostępnione publicznie: - Roni SternWięcej informacji
Dostępne w jakimś miejscu: 20
Multi-agent pathfinding: Definitions, variants, and benchmarks
R Stern, N Sturtevant, A Felner, S Koenig, H Ma, T Walker, J Li, D Atzmon, ...
Proceedings of the International Symposium on Combinatorial Search 10 (1 …, 2019
Upoważnienia: US National Science Foundation
Probabilistic robust multi-agent path finding
D Atzmon, R Stern, A Felner, NR Sturtevant, S Koenig
Proceedings of the International Conference on Automated Planning and …, 2020
Upoważnienia: US National Science Foundation
Modeling and solving the multi-agent pathfinding problem in picat
R Barták, NF Zhou, R Stern, E Boyarski, P Surynek
2017 IEEE 29th International Conference on Tools with Artificial …, 2017
Upoważnienia: US National Science Foundation
Towards a unifying framework for formal theories of novelty
T Boult, P Grabowicz, D Prijatelj, R Stern, L Holder, J Alspector, ...
Proceedings of the AAAI conference on artificial intelligence 35 (17), 15047 …, 2021
Upoważnienia: US Department of Defense
Learning Probably Approximately Complete and Safe Action Models for Stochastic Worlds
B Juba, R Stern
AAAI, 2022
Upoważnienia: US National Science Foundation, US Department of Defense
Safe multi-agent pathfinding with time uncertainty
T Shahar, S Shekhar, D Atzmon, A Saffidine, B Juba, R Stern
Journal of Artificial Intelligence Research 70, 923–954-923–954, 2021
Upoważnienia: US National Science Foundation
Greedy priority-based search for suboptimal multi-agent path finding
SH Chan, R Stern, A Felner, S Koenig
Proceedings of the International Symposium on Combinatorial Search 16 (1), 11-19, 2023
Upoważnienia: US National Science Foundation
Learning safe numeric action models
A Mordoch, B Juba, R Stern
Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 12079 …, 2023
Upoważnienia: US National Science Foundation, US Department of Defense
Predicting optimal solution costs with bidirectional stratified sampling in regular search spaces
LHS Lelis, R Stern, SJ Arfaee, S Zilles, A Felner, RC Holte
Artificial Intelligence 230, 51-73, 2016
Upoważnienia: Natural Sciences and Engineering Research Council of Canada
Safe Partial Diagnosis from Normal Observations
R Stern, B Juba
International Joint Conference on Artificial Intelligence (IJCAI), 2019
Upoważnienia: US National Science Foundation, US Department of Defense
Heuristic search for physics-based problems: angry birds in PDDL+
W Piotrowski, Y Sher, S Grover, R Stern, S Mohan
Proceedings of the International Conference on Automated Planning and …, 2023
Upoważnienia: US Department of Defense
Model-based adaptation to novelty for open-world AI
R Stern, W Piotrowski, M Klenk, J de Kleer, A Perez, J Le, S Mohan
Proceedings of the ICAPS Workshop on Bridging the Gap Between AI Planning …, 2022
Upoważnienia: US Department of Defense
Model-Based Novelty Adaptation for Open-World AI
M Klenk, W Piotrowski, R Stern, S Mohan, J de Kleer
International Workshop on Principles of Diagnosis (DX), 2020
Upoważnienia: US Department of Defense
Learning safe action models with partial observability
HS Le, B Juba, R Stern
Proceedings of the AAAI Conference on Artificial Intelligence 38 (18), 20159 …, 2024
Upoważnienia: US National Science Foundation
Online multi-agent path finding: New results
J Morag, A Felner, R Stern, D Atzmon, E Boyarski
Proceedings of the International Symposium on Combinatorial Search 15 (1 …, 2022
Upoważnienia: US National Science Foundation
Synthesizing priority planning formulae for multi-agent pathfinding
S Wang, V Bulitko, T Huang, S Koenig, R Stern
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2023
Upoważnienia: Natural Sciences and Engineering Research Council of Canada
An online approach for multi-agent path finding under movement uncertainty
E Levy, G Shani, R Stern
Proceedings of the International Symposium on Combinatorial Search 15 (1 …, 2022
Upoważnienia: US National Science Foundation
Multi-agent planning and diagnosis with commonsense reasoning
TC Son, W Yeoh, R Stern, M Kalech
Proceedings of the Fifth International Conference on Distributed Artificial …, 2023
Upoważnienia: US National Science Foundation
Safe Learning and Repairing of Numeric Action Models for Planning
AA Mordoch, B Juba, R Stern
33rd International Workshop on Principle of Diagnosis–DX 2022, 2022
Upoważnienia: US National Science Foundation
A System for Lifelong, Resilient, Job Shop Planning based on Learning Machine Capabilities from Operational Data
R Stern, W Piotrowski, LS Crawford, M Youngblood
Upoważnienia: US Department of Defense
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