Rolling Horizon Evolutionary Algorithm Improvements for General Video Game Playing in Single and Multi-Player Games
Artificial Intelligence is a field concerned with creating an agent capable of rational thought. When applied to games, the agent must be able to make decisions which would lead to fulfilling its goal (usually winning, possibly against an opponent). General Video Game Playing (GVGP) is a sub-field which 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. While Monte Carlo Tree Search (MCTS) has dominated GVGP, Rolling Horizon Evolutionary Algorithms (RHEA) have the potential to reach an even better performance. The proposed study will focus on improving RHEA, using mostly the GVG- AI framework for testing purposes. On successful completion, the research will have a great impact on the game industry, bringing forward better AI and new challenging experiences for players.
Home institution: Essex
Supervisor: Dr Diego Perez
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