一个使用遗传算法和人工群体智慧的填字游戏生成器

2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES) Pub Date : 2015-07-27 DOI:10.1109/CGames.2015.7272960

Douglas Bonomo, Adrian P. Lauf, Roman V. Yampolskiy

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引用次数: 6

摘要

np困难的问题，如生成填字游戏，是遗传算法(GAs)的候选解决方案。结合遗传算法和人工群体智慧(WoAC)聚合方法，开发了一种用于创建给定特定轮廓的填字游戏的组合方法。该程序是使用GPL Hunspell包装器NHunspell编写的，用于单词验证和建议。在美式填字游戏中，我们发现在达到局部最优时，GA + WoAC算法的性能提高了约20%，与基线遗传算法相比，GA + WoAC算法找到的成功单词数量提高了6%。

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A crossword puzzle generator using genetic algorithms with Wisdom of Artificial Crowds

NP-hard problems, such as generating crossword puzzles, are candidates for solution by genetic algorithms (GAs). A combination of both a genetic algorithms and a Wisdom of Artificial Crowds (WoAC) aggregation method was developed for the purpose of creating crossword puzzles given a particular outline. The program was written using a GPL Hunspell wrapper NHunspell for word verification and suggestion. In American-style crossword puzzles, we saw performance improvements of around 20% in reaching a local optima, with a 6% improvement in the number of successful words found by a GA + WoAC algorithm over the baseline genetic algorithm.

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2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)

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