  Computational models of emergent communication in agent populations are
currently gaining interest in the machine learning community due to recent
advances in Multi-Agent Reinforcement Learning (MARL). Current contributions
are however still relatively disconnected from the earlier theoretical and
computational literature aiming at understanding how language might have
emerged from a prelinguistic substance. The goal of this paper is to position
recent MARL contributions within the historical context of language evolution
research, as well as to extract from this theoretical and computational
background a few challenges for future research.
