A Study on Application of Reinforcement Learning in Game Test Automation

Abstract

To improve the efficiency of quality assurance and debugging tasks in game development, researches and developments for game test automation utilizing machine learning techniques have been promoted in recent years. In this study, we focus on the application of reinforcement learning to quality assurance tasks such as regression testing and game balancing, and discuss an efficient approach toward solving underlying issues for practical use.