General Game Heuristic Prediction Based on Ludeme Descriptions
This work addresses the challenge of selecting effective heuristics for general game playing, but it appears incremental as it builds on existing methods and data.
The paper tackled the problem of predicting heuristic performance in general game playing by training regression models on game descriptions from the Ludii system, achieving results based on performance data from various heuristics.
This paper investigates the performance of different general-game-playing heuristics for games in the Ludii general game system. Based on these results, we train several regression learning models to predict the performance of these heuristics based on each game's description file. We also provide a condensed analysis of the games available in Ludii, and the different ludemes that define them.