Towards generating arcade game rules with VGDL
Towards generating arcade game rules with VGDL
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使用 VGDL 生成街机游戏规则
DOI：
10.1109/cig.2015.7317941
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
M. Nelson
中科院分区：
文献类型：
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作者：
Thorbjørn S. Nielsen;Gabriella A. B. Barros;J. Togelius;M. Nelson
我们描述了一种尝试，以产生完整的街机游戏，使用视频游戏描述语言（VGDL）和通用视频游戏播放环境（GVG-AI）。游戏是由一个进化算法产生的基因型表示为VGDL描述。为了引导进化到好的游戏，我们需要一个评估函数来准确地评估游戏质量。这里使用的评估函数是基于几个游戏算法的差异性能，或相对算法性能配置文件（RAPP）：假设好的游戏允许好的玩家比坏的玩家玩得更好。为了进行这种评估，我们引入了两种新的游戏树搜索算法，DeepSearch和Explorer;这些算法在基准游戏上表现非常好，构成了本文的重要贡献。最终，生成街机游戏的尝试只取得了部分成功，因为一些游戏具有有趣的设计功能，但生成时几乎无法玩。这些缺点的分析产生了几个建议，以指导未来的尝试在街机游戏一代。
We describe an attempt to generate complete arcade games using the Video Game Description Language (VGDL) and the General Video Game Playing environment (GVG-AI). Games are generated by an evolutionary algorithm working on genotypes represented as VGDL descriptions. In order to direct evolution towards good games, we need an evaluation function that accurately estimates game quality. The evaluation function used here is based on the differential performance of several game-playing algorithms, or Relative Algorithm Performance Profiles (RAPP): it is assumed that good games allow good players to play better than bad players. For the purpose of such evaluations, we introduce two new game tree search algorithms, DeepSearch and Explorer; these perform very well on benchmark games and constitute a substantial subsidiary contribution of the paper. In the end, the attempt to generate arcade games is only partially successful, as some of the games have interesting design features but are barely playable as generated. An analysis of these shortcomings yields several suggestions to guide future attempts at arcade game generation.