@inproceedings{kottur-etal-2017-natural,
title = "Natural Language Does Not Emerge {`}Naturally{'} in Multi-Agent Dialog",
author = "Kottur, Satwik and
Moura, Jos{\'e} and
Lee, Stefan and
Batra, Dhruv",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D17-1321",
doi = "10.18653/v1/D17-1321",
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.",
}
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%0 Conference Proceedings
%T Natural Language Does Not Emerge ‘Naturally’ in Multi-Agent Dialog
%A Kottur, Satwik
%A Moura, José
%A Lee, Stefan
%A Batra, Dhruv
%S Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
%D 2017
%8 sep
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F kottur-etal-2017-natural
%X 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.
%R 10.18653/v1/D17-1321
%U https://aclanthology.org/D17-1321
%U https://doi.org/10.18653/v1/D17-1321
%P 2962-2967
Markdown (Informal)
[Natural Language Does Not Emerge ‘Naturally’ in Multi-Agent Dialog](https://aclanthology.org/D17-1321) (Kottur et al., EMNLP 2017)
ACL