Simply feeding the Slay the Spire game state directly to an LLM is currently insufficient to achieve stable deck-building or consistent combat performance.
I categorize the game's actions into three types: combat, deck-building, and other interactions.
For combat, MCTS is used. Yes, it's similar to the approach used in Go AI.
For deck-building, a sparse graph search is used: the goal is to rapidly identify winning deck templates within the graph structure.
Only the remaining aspects are delegated to the LLM to make reasoned decisions.
Simply feeding the Slay the Spire game state directly to an LLM is currently insufficient to achieve stable deck-building or consistent combat performance.
I categorize the game's actions into three types: combat, deck-building, and other interactions.
For combat, MCTS is used. Yes, it's similar to the approach used in Go AI.
For deck-building, a sparse graph search is used: the goal is to rapidly identify winning deck templates within the graph structure.
Only the remaining aspects are delegated to the LLM to make reasoned decisions.