Catalytic Role Of Noise And Necessity Of Inductive Biases In The Emergence Of Compositional CommunicationDownload PDF

May 21, 2021 (edited Jan 20, 2022)NeurIPS 2021 PosterReaders: Everyone
  • Keywords: compositionality, signaling games, noisy channel, deep learning
  • TL;DR: We show that inductive biases are needed for the emergence of compositional communication and that it emerges in signaling games in which agents communicate over a noisy channel.
  • Abstract: Communication is compositional if complex signals can be represented as a combination of simpler subparts. In this paper, we theoretically show that inductive biases on both the training framework and the data are needed to develop a compositional communication. Moreover, we prove that compositionality spontaneously arises in the signaling games, where agents communicate over a noisy channel. We experimentally confirm that a range of noise levels, which depends on the model and the data, indeed promotes compositionality. Finally, we provide a comprehensive study of this dependence and report results in terms of recently studied compositionality metrics: topographical similarity, conflict count, and context independence.
  • Supplementary Material: pdf
  • Code Of Conduct: I certify that all co-authors of this work have read and commit to adhering to the NeurIPS Statement on Ethics, Fairness, Inclusivity, and Code of Conduct.
  • Code: zip
12 Replies