Learning-Based Video Game Development in MLP@UoM: An Overview
This work targets video game developers and researchers by proposing a systematic approach to automate development, but it appears incremental as it builds on existing machine learning applications.
The paper overviews progress in applying machine learning to video game development at MLP@UoM, addressing challenges like game generation and intelligent agent creation to reduce labor and costs.
In general, video games not only prevail in entertainment but also have become an alternative methodology for knowledge learning, skill acquisition and assistance for medical treatment as well as health care in education, vocational/military training and medicine. On the other hand, video games also provide an ideal test bed for AI researches. To a large extent, however, video game development is still a laborious yet costly process, and there are many technical challenges ranging from game generation to intelligent agent creation. Unlike traditional methodologies, in Machine Learning and Perception Lab at the University of Manchester (MLP@UoM), we advocate applying machine learning to different tasks in video game development to address several challenges systematically. In this paper, we overview the main progress made in MLP@UoM recently and have an outlook on the future research directions in learning-based video game development arising from our works.