PhD Student, QMUL
I’m Cris; a Spanish in love with London, where I’ve been living since 2013. I studied a BE in Computer Engineering at Universidad Autónoma de Madrid (Spain) and worked as web developer for a couple of years before taking the decision of changing to the exciting world of AI and games. I am based in Queen Mary University of London and my research interests include General Video Game Playing (GVGP), Procedural Content Generation (PCG) and the study and development of different heuristics. I try to keep active outside the sedentary PhD live, mostly walking around the city, cycling and attempting different sports. Random facts are that I have a fascination with swords and my chosen superpower would be teleportation.
General video game playing agents to evaluate automatic generated levels
Procedural Content generation (PCG) refers to the generation of game content via automated processes. The validity of these artifacts should be checked to ensure their playability. Common approaches are game-specific and, although they ensure the playability of the generated content, they are limited by the game they are defined for. To solve this limitation, a strong connection between PCG and General Video Game (referring to algorithms that do not take game-specific knowledge into account) could be established, as general controllers could be used to validate content generated for any game.
The ultimate goal of Cristina’s research is creating a system capable of using General Video Game (GVG) agents to play and evaluate new automated generated levels for games. The evaluator would be formed by different controllers and would be capable of analyzing a provided level of a game without having any previous knowledge about the level or the game. The idea is giving an answer that would determine if a level should be included into the game or not, based on the expectations.