论文标题
自动化计算机游戏测试中的一种基于在线代理的搜索方法，并使用模型构建
An Online Agent-Based Search Approach in Automated Computer Game Testing with Model Construction
论文作者
论文摘要
电脑游戏的复杂性在不断提高。在此设置中，指导一种自动测试算法以找到在游戏的巨大交互空间中解决测试任务的解决方案非常具有挑战性。拥有一个自动生成测试用例的系统模型将对算法的有效性和效率产生重大影响。但是，手动构建模型却很昂贵且耗时。在这项研究中，我们提出了一种基于在线代理的搜索方法，以在测试计算机游戏时解决常见的测试任务，该计算机游戏还基于给定的任务构建系统模型，然后将利用该任务来解决该任务。为了证明我们方法的效率，使用称为实验室新兵的游戏进行案例研究。
The complexity of computer games is ever increasing. In this setup, guiding an automated test algorithm to find a solution to solve a testing task in a game's huge interaction space is very challenging. Having a model of a system to automatically generate test cases would have a strong impact on the effectiveness and efficiency of the algorithm. However, manually constructing a model turns out to be expensive and time-consuming. In this study, we propose an online agent-based search approach to solve common testing tasks when testing computer games that also constructs a model of the system on-the-fly based on the given task, which is then exploited to solve the task. To demonstrate the efficiency of our approach, a case study is conducted using a game called Lab Recruits.
