Research Post
Human designers may find it difficult to anticipate the impact of small changes to some games, particularly in puzzle games. However, it is not difficult for computers to simulate all mechanical impacts of such small changes. This suggests that computers might be able to aid humans designers as they build and analyze game levels.
This paper takes one step towards this larger goal by studying how Exhaustive Procedural Content Generation (EPCG) can be used for analysis of incremental changes of existing game levels. Using an incremental EPCG approach, we analyze all of the levels in the popular puzzle game Snakebird, showing that incremental variations in the level designs can significantly increase the length of the shortest possible solution.
A user study on a subset of these modified levels shows that the modified levels are both interesting and challenging for humans to play. Thus, through the analysis of Snakebird, we demonstrate the broader potential for incremental applications of EPCG.
Feb 24th 2022
Research Post
Feb 1st 2022
Research Post
Read this research paper, co-authored by Amii Fellow and Canada CIFAR AI Chairs Neil Burch and Michael Bowling: Rethinking formal models of partially observable multiagent decision making
Dec 6th 2021
Research Post
Read this research paper, co-authored by Amii Fellow and Canada CIFAR AI Chairs Neil Burch and Micheal Bowling: Player of Games
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