Codenames as a Game of Co-occurrence Counting

Réka Cserháti, István S. Kolláth, András Kicsi, Gábor Berend
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引用次数: 1

Abstract

Codenames is a popular board game, in which knowledge and cooperation between players play an important role. The task of a player playing as a spymaster is to find words (clues) that a teammate finds related to as many of some given words as possible, but not to other specified words. This is a hard challenge even with today’s advanced language technology methods.In our study, we create spymaster agents using four types of relatedness measures that require only a raw text corpus to produce. These include newly introduced ones based on co-occurrences, which outperform FastText cosine similarity on gold standard relatedness data. To generate clues in Codenames, we combine relatedness measures with four different scoring functions, for two languages, English and Hungarian. For testing, we collect decisions of human guesser players in an online game, and our configurations outperform previous agents among methods using raw corpora only.
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作为共现计数游戏的代号
《代号》是一款非常受欢迎的桌面游戏,玩家之间的知识和合作在其中扮演着重要的角色。扮演间谍大师的玩家的任务是找到队友发现的尽可能多的与某些给定单词相关的单词(线索),而不是与其他指定单词相关的单词。即使使用当今先进的语言技术方法,这也是一个艰巨的挑战。在我们的研究中,我们使用四种类型的相关性度量来创建间谍主代理,这些度量只需要生成原始文本语料库。其中包括新引入的基于共现的方法,它在黄金标准相关性数据上优于FastText余弦相似度。为了在代号中生成线索,我们将相关性测量与四种不同的评分函数结合起来,分别针对英语和匈牙利语两种语言。为了进行测试,我们收集了在线游戏中人类猜者的决策,我们的配置在仅使用原始语料库的方法中优于先前的代理。
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