The General Game Playing (GGP) problem is concerned with developing systems capable of playing many different games, even games the system has never encountered before. Successful GGP agents must be able to extract relevant features from the formal game description and construct effective search heuristics. In this article, we present a procedure by which autonomous General Game Playing agents can generate effective and efficient search heuristics from the formal game description. The major aspect of our approach is an innovative technique to automatically extract critical features from the game structure. Our method has been incorporated into a fully implemented system that came in fourth place at the second General Game Playing Competition held at AAAI-06.