Noisy Population Dynamics Lead to Efficiently Compressed Semantic Systems

Abstract

Converging cross-linguistic evidence suggests that that human vocabularies are shaped for efficient communication, but we know little about the agent-based dynamics that could explain their evolution. In this paper, we show that very general population dynamics of signaling games lead to the emergence of information-theoretically efficient meaning systems. In numerical simulations, we observe that noisy perception of meaning can result in evolved systems with higher efficiency.

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Cite

Text

Imel et al. "Noisy Population Dynamics Lead to Efficiently Compressed Semantic Systems." NeurIPS 2023 Workshops: InfoCog, 2023.

Markdown

[Imel et al. "Noisy Population Dynamics Lead to Efficiently Compressed Semantic Systems." NeurIPS 2023 Workshops: InfoCog, 2023.](https://mlanthology.org/neuripsw/2023/imel2023neuripsw-noisy/)

BibTeX

@inproceedings{imel2023neuripsw-noisy,
  title     = {{Noisy Population Dynamics Lead to Efficiently Compressed Semantic Systems}},
  author    = {Imel, Nathaniel and Futrell, Richard and Franke, Michael and Zaslavsky, Noga},
  booktitle = {NeurIPS 2023 Workshops: InfoCog},
  year      = {2023},
  url       = {https://mlanthology.org/neuripsw/2023/imel2023neuripsw-noisy/}
}