Mew World Order — An atomic theory of the Pokémon TCG
A model that sees cards as compositions of recurring elements, continuously learning and adapting in an ever-changing game. The Pokémon Trading Card Game is constantly changing. New cards are regularly released and the oldest are rotated out of format. The best players keep winning because they excel at adapting to the opportunities and constraints of each new format. Our approach is a system that can understand the game the same way. We entered the competition with three goals: We determined that rules-based agents would not achieve our goals, as there are too many situations to enumerate across deck archetypes. This led us to deep learning. We chose a transformer to let cards, game context, and legal actions interact through attention across the entire position. Attention excels at understanding “global context,” which we hypothesized would be useful for generalization over many cards. Pokémon’s board also lacks the spatial structure that motivates convolutions in games such as Go. W