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PaceMaker: A Practical Tool for Pacing Video Games

Julian Geheeb, Daniel Dyrda, Sebastian Geheeb

TL;DR

PaceMaker is presented, a toolkit designed to enable common design workflows for pacing while addressing the challenges above and demonstrates the expressiveness of the toolkit and support the need for such a tool.

Abstract

Designing pacing for video games presents a unique set of challenges. Due to their interactivity, non-linearity, and narrative nature, many aspects must be coordinated and considered simultaneously. In addition, games are often developed in an iterative workflow, making revisions to previous designs difficult and time-consuming. In this paper, we present PaceMaker, a toolkit designed to enable common design workflows for pacing while addressing the challenges above. We conducted initial research on pacing and then implemented our findings in a platform-independent application that allows the user to define simple state diagrams to deal with the possibility space of games. The user can select paths on the directed graph to visualize a node's data in diagrams dedicated to intensity and gameplay category. After implementation, we created a demonstration of the tool and conducted qualitative interviews. While the interviews raised some concerns about the efficiency of PaceMaker, the results https://info.arxiv.org/help/prep#commentsdemonstrate the expressiveness of the toolkit and support the need for such a tool.

PaceMaker: A Practical Tool for Pacing Video Games

TL;DR

PaceMaker is presented, a toolkit designed to enable common design workflows for pacing while addressing the challenges above and demonstrates the expressiveness of the toolkit and support the need for such a tool.

Abstract

Designing pacing for video games presents a unique set of challenges. Due to their interactivity, non-linearity, and narrative nature, many aspects must be coordinated and considered simultaneously. In addition, games are often developed in an iterative workflow, making revisions to previous designs difficult and time-consuming. In this paper, we present PaceMaker, a toolkit designed to enable common design workflows for pacing while addressing the challenges above. We conducted initial research on pacing and then implemented our findings in a platform-independent application that allows the user to define simple state diagrams to deal with the possibility space of games. The user can select paths on the directed graph to visualize a node's data in diagrams dedicated to intensity and gameplay category. After implementation, we created a demonstration of the tool and conducted qualitative interviews. While the interviews raised some concerns about the efficiency of PaceMaker, the results https://info.arxiv.org/help/prep#commentsdemonstrate the expressiveness of the toolkit and support the need for such a tool.
Paper Structure (24 sections, 3 equations, 5 figures, 1 table)

This paper contains 24 sections, 3 equations, 5 figures, 1 table.

Figures (5)

  • Figure 1: A pacing mindmap of the final definition. Here, the sub-categories are applied between the artifact and experience parameters. However, this sub-categorization can be applied on any level.
  • Figure 2: A replica of World 1-1 of Super Mario Bros. divided into 14 sections. Red dots correspond to enemies, green dots correspond to common power-ups, and the yellow dot corresponds to the star power-up.
  • Figure 3: The first five sections modeled in PaceMaker's experience chart during our walkthrough demonstration. A beat displays the name of the beat and a preview of the experience specification in the form of its name, the intensity value, and the gameplay category.
  • Figure 4: The remaining section to complete the model in PaceMaker's experience chart during our walkthrough demonstration. The leftmost beats overlap with \ref{['fig:mario_5_sections']}'s rightmost beats for continuity.
  • Figure 5: A showcase of PaceMaker's pacing diagrams of the demonstration with various settings. Top-left and bottom-left show the intensity diagram of the small--neutral route (path 1), the big--neutral route (path 2), and the flower--neutral route (path 3) with intensity settings Computed and different time settings. Top-middle shows the big--star route with intensity setting All. Top-right shows a comparison between the big--neutral route (path 1) and the big-hidden route (path 2) with intensity settings Computed. Bottom-middle and bottom-right show a neutral route (path 1), a star route (path 2), and a hidden route (path 3) on the category chart with different time settings.