论文标题
语言出现的内部和外部压力：努力最少，对象恒定和频率
Internal and external pressures on language emergence: least effort, object constancy and frequency
论文作者
论文摘要
在以前的工作中，人造代理在参考游戏中必须达到几乎完美的准确性，在他们必须进行交流以识别图像。然而，由此产生的通信协议很少显示自然语言的显着特征，例如构图。在本文中，我们提出了一些避免这种结果的沟通压力的现实压力。更具体地说，我们通过辅助目标正式将努力最少的原则正式化。此外，我们探索了几个游戏变体，灵感来自对象恒定的原理，在该原理中，我们改变了图像中对象的频率，位置和光度。我们通过组合性指标，诊断分类器和零摄像评估对其效果进行了广泛的分析。我们的发现表明，拟议的压力来源导致新兴语言的冗余性较小，更多地关注高级概念信息和更好的概括能力。总体而言，我们的贡献减少了新兴和自然语言之间的差距。
In previous work, artificial agents were shown to achieve almost perfect accuracy in referential games where they have to communicate to identify images. Nevertheless, the resulting communication protocols rarely display salient features of natural languages, such as compositionality. In this paper, we propose some realistic sources of pressure on communication that avert this outcome. More specifically, we formalise the principle of least effort through an auxiliary objective. Moreover, we explore several game variants, inspired by the principle of object constancy, in which we alter the frequency, position, and luminosity of the objects in the images. We perform an extensive analysis on their effect through compositionality metrics, diagnostic classifiers, and zero-shot evaluation. Our findings reveal that the proposed sources of pressure result in emerging languages with less redundancy, more focus on high-level conceptual information, and better abilities of generalisation. Overall, our contributions reduce the gap between emergent and natural languages.
