Emergent Communication in Multi-Agent Reinforcement Learning: A Survey

Abstract

We survey approaches to emergent communication in multi-agent reinforcement learning, organising them around the dimensions of language input, learning signal, and population structure. We argue that scaling toward human-language-like systems requires bridging emergent and natural-language research traditions.