In this paper, we propose a method and workflow for automating the testing of
certain video game aspects using automated planning and planning action model
learning techniques. The basic idea is to generate detailed gameplay logs and
apply action model learning to obtain a formal model in the planning domain
description language (PDDL). The workflow enables efficient cooperation of game
developers without any experience with PDDL or other formal systems and a
person experienced with PDDL modeling but no game development skills. We
describe the method and workflow in general and then demonstrate it on a
concrete proof-of-concept example -- a simple role-playing game provided as one
of the tutorial projects in the popular game development engine Unity. This
paper presents the first step towards minimizing or even eliminating the need
for a modeling expert in the workflow, thus making automated planning
accessible to a broader audience.

通过自动化测试和自动计划行动模型学习技术，本文提出了一种用于测试特定视频游戏方面的方法和工作流。该方法和工作流允许游戏开发人员和 PDDL 建模经验者之间的高效合作，以实现对计划领域描述语言 (PDDL) 的正式模型的生成，从而通过在 Unity 游戏开发引擎中提供的简单的角色扮演游戏的教程项目进行演示。本文是向流程中建模专家的职位需求降到最低甚至消除的第一步，从而使自动计划可以更广泛地被应用。