Learning-Based Video Game Development in MLP@UoM: An Overview

被引:0
|
作者
Chen, Ke [1 ]
机构
[1] Univ Manchester, Dept Comp Sci, Manchester M13 9PL, Lancs, England
关键词
video game development; machine learning; procedural content generation; serious education games; fast skill capture; learnable agent;
D O I
10.1109/iceeie47180.2019.8981430
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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.
引用
收藏
页码:358 / 363
页数:6
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