The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents

Understand

Since first introduced, computer simulation has been an increasingly important tool in evolutionary linguistics.

• Recently, with the development of deep learning techniques, research in grounded language learning has also started to focus on facilitating the emergence of compositional languages without pre-defined elementary linguistic knowledge.
• In this work, we explore the emergence of compositional languages for numeric concepts in multi-agent communication systems.
• We demonstrate that compositional language for encoding numeric concepts can emerge through iterated learning in populations of deep neural network agents.