Paying Attention to Function Words
It addresses a foundational linguistic problem about language evolution, but the approach is incremental as it builds on existing signaling game models.
The paper investigates the emergence of the universal distinction between content and function words in natural languages by demonstrating how it can arise through reinforcement learning in agents playing signaling games across contexts with multiple objects and properties.
All natural languages exhibit a distinction between content words (like nouns and adjectives) and function words (like determiners, auxiliaries, prepositions). Yet surprisingly little has been said about the emergence of this universal architectural feature of natural languages. Why have human languages evolved to exhibit this division of labor between content and function words? How could such a distinction have emerged in the first place? This paper takes steps towards answering these questions by showing how the distinction can emerge through reinforcement learning in agents playing a signaling game across contexts which contain multiple objects that possess multiple perceptually salient gradable properties.