Camila Aliaga, Cristian Vidal, Gabriel K. Sepulveda, Nicolas Romero, Fernanda González, Nicolas A. Barriga
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引用次数: 0
Abstract
Developing an original video game requires high investment levels, market research, cost-effective solutions, and a quick development process. Game developers usually reach for commercial off-the-shelf components often available in the engine's marketplace to reduce costs. Mixed-initiative authoring tools allow us to combine the thoughtful work of human designers with the productivity gains of automated techniques. However, most commercial AI-assisted Procedural Content Generation tools focus on generating small independent components, and standalone research tools available for generating full game levels with state-of-the-art algorithms usually lack integration with commercial game engines. This article aims to fill this gap between industry and academia. The Level Building Sidekick (LBS) is a mixed-initiative procedural content generation tool built by our research lab in association with four small independent game studios. It has a modular software architecture that enables developers to extend it for their particular projects. The current version has two working modules for building game maps, an early version of a module for populating the level with NPCs or items, and the first stages of a quest editor module. An automated testing module is planned. LBS is distributed as an AI-Assisted videogame-level editor Unity package. Usability testing performed using the ``Think-Aloud'' methodology indicates LBS has the potential to improve game development processes convincingly. However, at this stage, the user interface and the AI recommendations could improve their intuitiveness. As a general comment, the tool is perceived as a substantial contribution to facilitating and shortening development times, compared to only using the base game engine. There is an untapped market for mixed-initiative tools that assist the game designer in creating complete game levels. We expect to fill that market for our partner development studios and provide the community with an open research and development platform in a standard game engine.
开发一款原创电子游戏需要高投入、市场调研、高性价比的解决方案和快速的开发过程。游戏开发者通常会利用引擎市场上的现成组件来降低成本。混合创作工具允许我们将人类设计师深思熟虑的工作与自动化技术的生产力收益结合起来。然而,大多数商业ai辅助的程序内容生成工具专注于生成小型独立组件,而用于生成具有最先进算法的完整游戏关卡的独立研究工具通常缺乏与商业游戏引擎的集成。本文旨在填补工业界和学术界之间的这一空白。Level Building Sidekick (LBS)是我们的研究实验室与四家小型独立游戏工作室联合开发的一款混合主动程序内容生成工具。它有一个模块化的软件体系结构,使开发人员能够为他们的特定项目扩展它。当前版本有两个用于创建游戏地图的工作模块,一个早期版本的模块用于用npc或道具填充关卡,以及一个任务编辑器模块的第一阶段。计划一个自动化测试模块。LBS是作为ai辅助视频游戏关卡编辑器Unity包发布的。使用“Think-Aloud”方法进行的可用性测试表明,LBS具有令人信服地改善游戏开发过程的潜力。然而,在这个阶段,用户界面和人工智能建议可以提高它们的直观性。总的来说,与只使用基本游戏引擎相比,该工具被认为对促进和缩短开发时间做出了重大贡献。帮助游戏设计师创造完整游戏关卡的混合主动工具还有一个未开发的市场。我们希望为合作开发工作室填补这个市场,并在标准游戏引擎上为社区提供一个开放的研发平台。