论文标题
Crea.blender：一种基于神经网络的图像生成游戏，用于评估创造力
crea.blender: A Neural Network-Based Image Generation Game to Assess Creativity
论文作者
论文摘要
我们介绍了一项关于Crea.Blender的试点研究，这是一种新型的共同创造游戏，旨在对人类创造力的不同结构进行大规模的系统评估。共同创造的系统是人类和计算机（通常与机器学习）协作创造性任务的系统。这种人类计算机的合作提出了有关人类创造力和参与过程中的相关性和水平的疑问。我们在这项试点研究中扩展并探讨这些问题的各个方面。我们观察参与者通过Crea.blender中的三种不同的游戏模式进行游戏，每个游戏都与既定的创造力评估方法一致。在这些模式下，玩家将现有图像“将”“融合”到不同约束下的新图像中。我们的研究表明，Crea.blender提供了嬉戏的体验，为玩家提供了对界面的控制感，并引起了不同类型的玩家行为，支持进一步研究该工具以进行可扩展，有趣，创造力评估。
We present a pilot study on crea.blender, a novel co-creative game designed for large-scale, systematic assessment of distinct constructs of human creativity. Co-creative systems are systems in which humans and computers (often with Machine Learning) collaborate on a creative task. This human-computer collaboration raises questions about the relevance and level of human creativity and involvement in the process. We expand on, and explore aspects of these questions in this pilot study. We observe participants play through three different play modes in crea.blender, each aligned with established creativity assessment methods. In these modes, players "blend" existing images into new images under varying constraints. Our study indicates that crea.blender provides a playful experience, affords players a sense of control over the interface, and elicits different types of player behavior, supporting further study of the tool for use in a scalable, playful, creativity assessment.
