We introduce STORY2GAME, a novel approach to using Large Language Models to generate text-based interactive fiction games that starts by generating a story, populates the world, and builds the code for actions in a game engine that enables the story to play out interactively. Whereas a given set of hard-coded actions can artificially constrain story generation, the ability to generate actions means the story generation process can be more open-ended but still allow for experiences that are grounded in a game state. The key to successful action generation is to use LLM-generated preconditions and effects of actions in the stories as guides for what aspects of the game state must be tracked and changed by the game engine when a player performs an action. We also introduce a technique for dynamically generating new actions to accommodate the player's desire to perform actions that they think of that are not part of the story. Dynamic action generation may require on-the-fly updates to the game engine's state representation and revision of previously generated actions. We evaluate the success rate of action code generation with respect to whether a player can interactively play through the entire generated story.

翻译：我们提出了STORY2GAME，这是一种利用大型语言模型生成基于文本的交互式虚构游戏的新方法。该方法首先生成一个故事，填充游戏世界，并为游戏引擎中的动作构建代码，使得故事能够以交互方式展开。与一组固定的硬编码动作可能人为限制故事生成不同，生成动作的能力意味着故事生成过程可以更加开放，同时仍能确保体验基于游戏状态。成功生成动作的关键在于，利用大型语言模型生成故事中动作的前提条件和效果，作为指导游戏引擎在玩家执行动作时必须跟踪和改变游戏状态哪些方面的依据。我们还引入了一种动态生成新动作的技术，以适应玩家希望执行其想到的、但不在原故事中的动作的需求。动态动作生成可能需要实时更新游戏引擎的状态表示，并修订先前生成的动作。我们评估了动作代码生成的成功率，依据是玩家能否以交互方式完整地体验整个生成的故事。