Deep Learning Techniques for Explainable Resource Scales in Collectible Card Games

In collectible card games, developers face the challenge of creating new, and interesting cards that are not too strong or game-breaking, retaining the game’s overall balance. Over time, this becomes challenging due to the sheer volume of the published content. In this article, we propose a framework for generating models capable of recommending resource scales, a pivotal point in balancing. We ev...