CNN-based Game State Detection for a Foosball Table

arXiv:2404.05357v1 Announce Type: new
Abstract: The automation of games using Deep Reinforcement Learning Strategies (DRL) is a well-known challenge in AI research. While for feature extraction in a video game typically the whole image is used, this is hardly practical for many real world games. Instead, using a smaller game state reducing the dimension of the parameter space to include essential parameters only seems to be a promising approach. In the game of Foosball, a compact and comprehensive game state …

abstract ai research arxiv automation challenge cnn cs.cv detection extraction feature feature extraction game games image practical reinforcement reinforcement learning research state strategies table type video video game world