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GTP-Force: Game-Theoretic Trajectory Prediction through Dis..:
, In:
2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
,
Emami, Negar
;
Di Maio, Antonio
;
Braun, Torsten
- p. 234-242 , 2023
Link:
https://doi.org/10.1109/MASS58611.2023.00036
RT T1
2023 IEEE 20th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
: T1
GTP-Force: Game-Theoretic Trajectory Prediction through Distributed Reinforcement Learning
UL https://suche.suub.uni-bremen.de/peid=ieee-10298375&Exemplar=1&LAN=DE A1 Emami, Negar A1 Di Maio, Antonio A1 Braun, Torsten YR 2023 SN 2155-6814 K1 Training K1 Pedestrians K1 Neural networks K1 Collaboration K1 Reinforcement learning K1 Games K1 Predictive models K1 Trajectory Prediction K1 Multi-Agent Social Interactions K1 Transformers K1 Reinforcement Learning K1 Neural Architecture Search K1 Non-cooperative Game Theory K1 Clustering SP 234 OP 242 LK http://dx.doi.org/https://doi.org/10.1109/MASS58611.2023.00036 DO https://doi.org/10.1109/MASS58611.2023.00036 SF ELIB - SuUB Bremen
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