(Deep) Reinforcement Learning, Machine Learning
Autonomous Agents, Multi-Agent, ystems, Computer Vision
Christos Spatharis acquired his B.Sc. in Computer Science & Engineering from University of Ioannina and his M.Sc. in Technologies – Applications (in the area of Machine Learning and Reinforcement Learning) from the same Department. The title of his M.Sc. thesis was “Multi-Agent Reinforcement Learning Methods”. He is currently a Ph.D. Student in the Department of Computer Science & Engineering at University of Ioannina. During his academic career so far, he took part in the DART research program and is currently working in “Data-Driven Trajectory Imitation with Reinforcement Learning” project. Moreover, he participated in the publication of four (4) research papers and presented two (2) of them at SETN (2018) and IISA (2019) conferences. His research interests include (Deep) Reinforcement Learning, Machine Learning, Autonomous Agents, Multi-Agent Systems and Computer Vision.
Collaborative multiagent reinforcement learning schemes for air traffic management Conference
IISA 2019, 2019.
Multiagent Reinforcement Learning Methods to Resolve Demand Capacity Balance Problems Proceeding
Multiagent Reinforcement Learning Methods for Resolving Demand – Capacity Imbalances Conference
DASC 2018, London, UK, 2018.
Learning Policies for Resolving Demand-Capacity Imbalances during Pre-tactical Air Traffic Management Proceeding