Game-Agnostic Value Functions through Automatic JSON Feature Extraction
This work introduces JSON-Bag VF, a game-agnostic approach to training value functions for game-playing agents using JSON-Bag prototypes that can be enhanced with Random Forest-based feature selection and a method to select game-stage-specific features.
Dien Nguyen, Diego Pérez-Liébana
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