Raluca D. Gaina is currently studying for her Ph.D. in Intelligent Games and Games Intelligence at Queen Mary University of London, in the area of rolling horizon evolution in general video game playing, after completing a B.Sc. and M.Sc. in Computer Games at the University of Essex. In 2018, she did a 3 month internship at Microsoft Research Cambridge, working on the Multi-Agent Reinforcement Learning in Malmo Competition (MARLO). She was the track organiser of the Two-Player General Video Game AI Competition (GVGAI) 2016-2019 and is the Vice-Chair of the IEEE CIS Games Technical Committee in 2020. Her research interests include general video game playing AI, reinforcement learning and evolutionary computation algorithms.
Raluca’s research is focused on Rolling Horizon Evolutionary Algorithms (RHEA), which show promise to outperform the dominating Monte Carlo Tree Search in the area of general video game playing. As a sub-field of Artificial Intelligence, general video game playing aims to design an agent which would achieve high-level play in any given game, thus raising the need to generalize the heuristics used and introduce various machine learning techniques to gather information about the previously unknown game. So far, various aspects have been explored in several games, such as the impact of the hyper parameters on performance; population seeding techniques; and other algorithm structure modifications previously encountered in literature, now tested in a consistent environment and a general setting. On successful completion, the research aims to bring forward better NPCs and new challenging experiences for players, as well as reliable game testing tools.