Developing an Open-Source Lightweight Game Engine with DNN Support

被引:3
|
作者
Park, Haechan [1 ]
Baek, Nakhoon [1 ,2 ]
机构
[1] Kyungpook Natl Univ, Sch Comp Sci & Engn, Daegu 41566, South Korea
[2] Louisiana State Univ, Sch Elect Engn & Comp Sci, Baton Rouge, LA 70803 USA
基金
新加坡国家研究基金会;
关键词
game engine; open source; artificial intelligence; light-weight; deep neural network; implementation; case study;
D O I
10.3390/electronics9091421
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the growth of artificial intelligence and deep learning technology, we have many active research works to apply the related techniques in various fields. To test and apply the latest machine learning techniques in gaming, it will be very useful to have a light-weight game engine for quick prototyping. Our game engine is implemented in a cost-effective way, in comparison to well-known commercial proprietary game engines, by utilizing open source products. Due to its simple internal architecture, our game engine is especially beneficial for modifying and reviewing the new functions through quick and repetitive tests. In addition, the game engine has a DNN (deep neural network) module, with which the proposed game engine can apply deep learning techniques to the game features, through applying deep learning algorithms in real-time. Our DNN module uses a simple C++ function interface, rather than additional programming languages and/or scripts. This simplicity enables us to apply machine learning techniques more efficiently and casually to the game applications. We also found some technical issues during our development with open sources. These issues mostly occurred while integrating various open source products into a single game engine. We present details of these technical issues and our solutions.
引用
收藏
页码:1 / 15
页数:15
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