PhD student
Theocharis Kravaris
Researcher
Research Interests
Deep Reinforcement Learning, Multi-agent Systems, Neural Networks, Machine Learning
Contact
Additional Information
Theocharis Kravaris is a PhD candidate, researching Multi-agent Deep Reinforcement Learning, at the Department of Digital Systems in the University of Piraeus, under the supervision of Prof. George Vouros. He graduated (2017) as a MSc. student at the Department of Informatics and Telecommunications of the National and Kapodistrian University of Athens with a Specialization of Information and Data Management, having received his bachelor’s degree (2015) in the same department, at the Track of Computer Systems and Applications. He has served as teaching assistant on Artificial Intelligence (2016, 2017, 2018), Advanced Artificial Intelligence (2018), Intelligent Agent Systems (2018) and Data Structures (2016). He became a member of the University of Piraeus’s AI Lab (2017) and participated in the DART project (SESAR project), starting with his Post-grad thesis, titled Collaborative Reinforcement Learning for Resolving Hotspots in the Air Traffic Management Domain, until the end of the project. He is working on the Engage Catalyst project since June 2019
Publications
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} } |
2018 |
Calvo, Esther; Cordero, Jose Manuel; Chalkiadakis, Georgios; Spatharis, Christos; Kravaris, Theocharis; Vouros, George; Blekas, Konstantinos Multiagent Reinforcement Learning Methods to Resolve Demand Capacity Balance Problems Proceeding 2018. @proceedings{334, title = {Multiagent Reinforcement Learning Methods to Resolve Demand Capacity Balance Problems}, author = {Esther Calvo and Jose Manuel Cordero and Georgios Chalkiadakis and Christos Spatharis and Theocharis Kravaris and George Vouros and Konstantinos Blekas}, year = {2018}, date = {2018-01-01}, journal = {Hellenic Artificial Intelligence Conference (SETN)}, keywords = {}, pubstate = {published}, tppubtype = {proceedings} } |
Spatharis, Christos; Kravaris, Theocharis; Blekas, Konstantinos; Vouros, George A Multiagent Reinforcement Learning Methods for Resolving Demand – Capacity Imbalances Conference DASC 2018, London, UK, 2018. @conference{337, title = {Multiagent Reinforcement Learning Methods for Resolving Demand – Capacity Imbalances}, author = {Christos Spatharis and Theocharis Kravaris and Konstantinos Blekas and George A Vouros}, year = {2018}, date = {2018-00-01}, booktitle = {DASC 2018}, address = {London, UK}, keywords = {}, pubstate = {published}, tppubtype = {conference} } |
2017 |
Garcia, Jose Manuel Cordero; Chalkiadakis, Georgios; Kravaris, Theocharis; Vouros, George A; Spatharis, Christos; Blekas, Konstantinos Learning Policies for Resolving Demand-Capacity Imbalances during Pre-tactical Air Traffic Management Proceeding Springer, 2017. @proceedings{325, title = {Learning Policies for Resolving Demand-Capacity Imbalances during Pre-tactical Air Traffic Management}, author = {Jose Manuel Cordero Garcia and Georgios Chalkiadakis and Theocharis Kravaris and George A Vouros and Christos Spatharis and Konstantinos Blekas}, year = {2017}, date = {2017-01-01}, journal = {MATES 2017}, publisher = {Springer}, keywords = {}, pubstate = {published}, tppubtype = {proceedings} } |