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Open AccessArticle

Developing an Open-Source Lightweight Game Engine with DNN Support

by and *,†
School of Computer Science and Engineering, Kyungpook National University, Daegu 41566, Korea
*
Author to whom correspondence should be addressed.
Currently visiting: School of Electrical Engineering & Computer Science, Louisiana State University, Baton Rouge, LA 70803, USA.
Electronics 2020, 9(9), 1421; https://doi.org/10.3390/electronics9091421
Received: 15 June 2020 / Revised: 9 July 2020 / Accepted: 13 July 2020 / Published: 1 September 2020
(This article belongs to the Special Issue Ambidextrous Open Innovation of Electronics)
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. View Full-Text
Keywords: game engine; open source; artificial intelligence; light-weight; deep neural network; implementation; case study game engine; open source; artificial intelligence; light-weight; deep neural network; implementation; case study
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MDPI and ACS Style

Park, H.; Baek, N. Developing an Open-Source Lightweight Game Engine with DNN Support. Electronics 2020, 9, 1421. https://doi.org/10.3390/electronics9091421

AMA Style

Park H, Baek N. Developing an Open-Source Lightweight Game Engine with DNN Support. Electronics. 2020; 9(9):1421. https://doi.org/10.3390/electronics9091421

Chicago/Turabian Style

Park, Haechan; Baek, Nakhoon. 2020. "Developing an Open-Source Lightweight Game Engine with DNN Support" Electronics 9, no. 9: 1421. https://doi.org/10.3390/electronics9091421

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