用GUR绘制未知地图:AI测试如何补充专家评估

Atiya Nova, S. Sansalone, R. Robinson, Pejman Mirza-Babaei
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引用次数: 1

摘要

尽管将专家评估作为游戏用户研究(GUR)的一种方法具有优势(即为利益相关者提供低成本,快速的反馈),但它并不总是能够准确地反映一般玩家的体验。让真实用户测试游戏(游戏邦注:也称为游戏测试)能够帮助游戏开发者深入了解玩家体验,从而弥补这一差距。然而,游戏测试需要耗费大量资源和时间,因此很难在行业游戏开发的紧迫时间框架内实施。AI可以通过提供一种自动模拟玩家行为和体验的方法来缓解这些问题。在本文中,我们将介绍一种名为PathOS+的工具,这是一种使用AI游戏测试数据来帮助提高专家评估的游戏测试界面。一项由专家参与的研究结果表明,PathOS+可以为游戏设计做出贡献,并帮助开发者和研究人员进行专家评估。这是一个重要的贡献,因为它为游戏用户研究人员和设计师提供了一种快速、低成本和有效的游戏评估方法,这有可能使独立和小型游戏工作室更容易进行游戏评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Charting the Uncharted with GUR: How AI Playtesting Can Supplement Expert Evaluation
Despite the advantages of using expert evaluation as a method within games user research (GUR) (i.e. provides stakeholders low cost, rapid feedback), it does not always accurately reflect the general player’s experience. Testing the game out with real users (also called playtesting) helps bridge this gap by giving game developers an in-depth look into the player experience. However, playtesting is resource intensive and time consuming, making it difficult to implement within the tight time frames of industry game development. AI can help to mitigate some of these issues by providing an automated way to simulate player behaviour and experience. In this paper, we introduce a tool called PathOS+—a playtesting interface which uses AI playtesting data to help enhance expert evaluation. Results from a study conducted with expert participants shows how PathOS+ could contribute to game design and assist developers and researchers in conducting expert evaluations. This is an important contribution as it provides game user researchers and designers with a fast, low-cost and effective game evaluation approach which has the potential to make game evaluation more accessible to indie and smaller game studios.
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