The domain of text-based adventure games has been recently established as a new challenge of creating the agent that is both able to understand natural language, and acts intelligently in text-described environments. In this paper, we present our approach to tackle the problem. Our agent, named Golovin, takes advantage of the limited game domain. We use genre-related corpora (including fantasy books and decompiled games) to create language models suitable to this domain. Moreover, we embed mechanisms that allow us to specify, and separately handle, important tasks as fighting opponents, managing inventory, and navigating on the game map. We validated usefulness of these mechanisms, measuring agent's performance on the set of 50 interactive fiction games. Finally, we show that our agent plays on a level comparable to the winner of the last year Text-Based Adventure AI Competition.

本篇论文主要介绍了我们的方法来解决文本冒险游戏中需要理解自然语言并在游戏中表现出智能行为的代理问题。我们的代理Golovin利用游戏领域的限制，利用相关文献和游戏来创建适用于该领域的语言模型。此外，我们还嵌入了机制，以便我们可以指定和分别处理重要的任务，如对手作战，管理库存和在游戏地图上导航，并通过测量代理在50个互动小说游戏集中的表现来验证了这些机制的有效性。最后，我们展示了我们的代理在Text-Based Adventure AI比赛中使我们获得了与去年获胜者相当的成绩。

Golovin AI代理的基于文本的冒险