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Interactive Visualizer to Facilitate Game Designers in Understanding Machine Learning

Published: 02 May 2019 Publication History

Abstract

Machine Learning (ML) is a useful tool for modern game designers but often requires a technical background to understand. This gap of knowledge can intimidate less technical game designers from employing ML techniques to evaluate designs or incorporate ML into game mechanics. Our research aims to bridge this gap by exploring interactive visualizations as a way to introduce ML principles to game designers. We have developed QUBE, an interactive level designer that shifts ML education into the context of game design. We present QUBE's interactive visualization techniques and evaluation through two expert panels (n=4, n=6) with game design, ML, and user experience experts.

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Cited By

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  • (2022)Tooling for Developing Data-Driven Applications: Overview and OutlookProceedings of Mensch und Computer 202210.1145/3543758.3543779(66-77)Online publication date: 4-Sep-2022
  • (2022)Danesh: Interactive Tools for Understanding Procedural Content GeneratorsIEEE Transactions on Games10.1109/TG.2021.307832314:3(329-338)Online publication date: Sep-2022
  • (2021)Human-XAI Interaction: A Review and Design Principles for Explanation User InterfacesHuman-Computer Interaction – INTERACT 202110.1007/978-3-030-85616-8_36(619-640)Online publication date: 26-Aug-2021

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      cover image ACM Conferences
      CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
      May 2019
      3673 pages
      ISBN:9781450359719
      DOI:10.1145/3290607
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Published: 02 May 2019

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      Author Tags

      1. game design
      2. interactive visualizations
      3. machine learning

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      View all
      • (2022)Tooling for Developing Data-Driven Applications: Overview and OutlookProceedings of Mensch und Computer 202210.1145/3543758.3543779(66-77)Online publication date: 4-Sep-2022
      • (2022)Danesh: Interactive Tools for Understanding Procedural Content GeneratorsIEEE Transactions on Games10.1109/TG.2021.307832314:3(329-338)Online publication date: Sep-2022
      • (2021)Human-XAI Interaction: A Review and Design Principles for Explanation User InterfacesHuman-Computer Interaction – INTERACT 202110.1007/978-3-030-85616-8_36(619-640)Online publication date: 26-Aug-2021

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