论文标题
通过创意机器学习（GDCML）迈向游戏设计
Towards Game Design via Creative Machine Learning (GDCML)
论文作者
论文摘要
近年来，机器学习（ML）系统越来越多地用于执行创意任务。这种创意的ML方法已在视觉艺术和音乐领域广泛使用，例如图像，音乐发电和风格转移。但是，尽管出现了基于ML的方法来生成游戏内容，但在游戏设计领域中类似的创意ML技术并未被广泛采用。在本文中，我们主张利用和重新利用这种为游戏设计内容的创意技术，将其称为通过Creative ML（GDCML）的游戏设计方法。我们强调了现有的系统，这些系统可以启用GDCML并说明Creative ML如何通过示例应用程序和拟议的系统告知新系统。
In recent years, machine learning (ML) systems have been increasingly applied for performing creative tasks. Such creative ML approaches have seen wide use in the domains of visual art and music for applications such as image and music generation and style transfer. However, similar creative ML techniques have not been as widely adopted in the domain of game design despite the emergence of ML-based methods for generating game content. In this paper, we argue for leveraging and repurposing such creative techniques for designing content for games, referring to these as approaches for Game Design via Creative ML (GDCML). We highlight existing systems that enable GDCML and illustrate how creative ML can inform new systems via example applications and a proposed system.
