Our work focuses on developing and evaluating enhanced inverse reinforcement learning and imitation learning methods regarding 4D trajectories, although not only for those trajectories. Thus, we follow a supervised leaning approach, and treat historical data provided by “experts” as demonstrations that a machine learning algorithm should exploit to learn the corresponding models of costs/rewards and action policies. Then, learned models can be exploited to plan or predict trajectories.
Specific Topics
- Imitation & Inverse Reinforcement Learning with Deep Machine Learning Methods
- Modelling and Doing Analytics with Trajectories in the Transportation Domain
Recent Publications
2020 |
Vouros, George A; Glenis, Apostolis; Doulkeridis, Christos The delta big data architecture for mobility analytics Conference 2020 IEEE Sixth International Conference on Big Data Computing Service and Applications (BigDataService), IEEE IEEE, Oxford, UK, 2020. @conference{359, title = {The delta big data architecture for mobility analytics}, author = {George A Vouros and Apostolis Glenis and Christos Doulkeridis}, year = {2020}, date = {2020-01-01}, booktitle = {2020 IEEE Sixth International Conference on Big Data Computing Service and Applications (BigDataService)}, publisher = {IEEE}, address = {Oxford, UK}, organization = {IEEE}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
2019 |
Kravaris, Theocharis; et al., Resolving Congestions in the Air Traffic Management Domain via Multiagent Reinforcement Learning Methods Journal Article arXiv, cs.MA , 2019. @article{354, title = {Resolving Congestions in the Air Traffic Management Domain via Multiagent Reinforcement Learning Methods}, author = {Theocharis Kravaris and et al.}, url = {https://arxiv.org/pdf/1912.06860.pdf}, year = {2019}, date = {2019-12-01}, journal = {arXiv}, volume = {cs.MA}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
G.Vouros, ; Santipantakis, G; Doulkeridis, C; Vlachou, A; Andrienko, G; Andrienko, N; Fuchs, G; Martinez, Miguel Garcia; Cordero, Jose Manuel Garcia Journal Of Data Semantics, 8 , 2019. @article{352, title = {The datAcron Ontology for the Specification of Semantic Trajectories: Specification of Semantic Trajectories for Data Transformations Supporting Visual Analytics}, author = {G.Vouros and G Santipantakis and C Doulkeridis and A Vlachou and G Andrienko and N Andrienko and G Fuchs and Miguel Garcia Martinez and Jose Manuel Garcia Cordero}, url = {http://link.springer.com/article/10.1007/s13740-019-00108-0}, doi = {10.1007/s13740-019-00108-0}, year = {2019}, date = {2019-11-01}, journal = {Journal Of Data Semantics}, volume = {8}, chapter = {235}, keywords = {}, pubstate = {published}, tppubtype = {article} } |
Petrou, P; et al., ARGO: A Big Data Framework for Online Trajectory Prediction Conference SSTD 2019, 2019. @conference{345, title = {ARGO: A Big Data Framework for Online Trajectory Prediction}, author = {P Petrou and et al.}, year = {2019}, date = {2019-01-01}, booktitle = {SSTD 2019}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
Doulkeridis, Christos; Qu, Qiang; Vouros, George A; ~a, Jo Guest Editorial: Special issue on mobility analytics for spatio-temporal and social data. Journal Article GEOINFORMATICA, 23 , 2019. @article{353, title = {Guest Editorial: Special issue on mobility analytics for spatio-temporal and social data.}, author = {Christos Doulkeridis and Qiang Qu and George A Vouros and Jo ~a}, url = {https://link.springer.com/article/10.1007%2Fs10707-019-00374-x}, year = {2019}, date = {2019-01-01}, journal = {GEOINFORMATICA}, volume = {23}, chapter = {235}, keywords = {}, pubstate = {published}, tppubtype = {article} } |