作者: Nathan Sturtevant , Matthew Guzdial , Nicolas Decroocq , Aaron Tripodi
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摘要: Human designers may find it difficult to anticipate the impact of small changes some games, particularly in puzzle games. However, is not for computers simulate all mechanical impacts such changes. This suggests that might be able aid humans as they build and analyze game levels. paper takes one step towards this larger goal by studying how Exhaustive Procedural Content Generation (EPCG) can used analysis incremental existing Using an EPCG approach, we levels popular Snakebird, showing variations level designs significantly increase length shortest possible solution. A user study on a subset these modified shows are both interesting challenging play. Thus, through demonstrate broader potential applications EPCG.