We introduce FiLex, a self-reinforcing stochastic process which models finite lexicons in emergent language experiments. The central property of FiLex is that it is a self-reinforcing process, parallel to the intuition that the more a word is used in a language, the more its use will continue. As a theoretical model, FiLex serves as a way to both explain and predict the behavior of the emergent language system. We empirically test FiLex's ability to capture the relationship between the emergent language's hyperparameters and the lexicon's Shannon entropy.

翻译：我们引入了FiLex, 这是一种自我强化的随机过程, 它在突发语言实验中模拟了有限词典。 FiLex的核心特性是它是一个自我强化的过程, 与一个词在一种语言中使用越多的直觉平行, 它的使用就越持续。 作为一个理论模型, FiLex 是一个解释和预测突发语言系统行为的方法。 我们从经验上测试了 FiLex 捕捉突发语言的超参数和词典的香农 entropy 之间的关系的能力 。