描述
Our machine learning is being applied to tabletop role-playing games (TTRPGs). Were using it generate non-player characters (NPCs) and monsters for use in the game. This involves training a machine learning model on a dataset of NPC or monster descriptions, and using the model to generate new, unique NPCs or monsters on the fly. Another we are using machine learning to help balance game mechanics, such as by predicting the outcomes of different in-game actions or by suggesting changes to game rules to make the game more fair and enjoyable.
Other potential applications of machine learning in TTRPGs include using machine learning to generate game content (such as puzzles or quests), to generate dialogue for NPCs, or to help GMs run their games more efficiently (for example, by suggesting which NPCs or locations to use in a given scenario). However, it is important to note that the use of machine learning in TTRPGs is still an area of active research and development, and it is likely that new and creative ways of using machine learning in these types of games will continue to be explored in the future. We hope to remain on the frontlines of the field
