@InProceedings{kottur-EtAl:2017:EMNLP2017,
  author    = {Kottur, Satwik  and  Moura, Jos\'{e}  and  Lee, Stefan  and  Batra, Dhruv},
  title     = {Natural Language Does Not Emerge ‘Naturally’ in Multi-Agent Dialog},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {2962--2967},
  abstract  = {A number of recent works have proposed techniques for end-to-end learning of
	communication protocols among cooperative multi-agent populations, and have
	simultaneously found the emergence of grounded human-interpretable language in
	the protocols developed by the agents, learned without any human supervision!
	In this paper, using a Task \& Talk reference game between two agents as a
	testbed,  we present a sequence of `negative' results culminating in a
	`positive' one -- showing that while most agent-invented languages are
	effective (i.e. achieve near-perfect task rewards), they are decidedly not
	interpretable or compositional. In essence, we find that natural language does
	not emerge `naturally',despite the semblance of ease of
	natural-language-emergence that one may gather from recent literature. We
	discuss how it is possible to coax the invented languages to become more and
	more human-like and compositional by increasing restrictions on how two agents
	may communicate.},
  url       = {https://www.aclweb.org/anthology/D17-1321}
}