# From Language Games to Drawing Games

arXiv: https://arxiv.org/abs/2010.02820 · HTML: https://mlsanity.com/paper/2010.02820/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Oct 2020.

## Built on by (most cited first, 5 of 5)

- [Learning to Draw: Emergent Communication through Sketching](https://mlsanity.com/paper/2106.02067/) (2021)
- [The Five Ws of Multi-Agent Communication: Who Talks to Whom, When, What, and Why -- A Survey from MARL to Emergent Language and LLMs](https://mlsanity.com/paper/2602.11583/) (2026)
- [Generative Art Using Neural Visual Grammars and Dual Encoders](https://mlsanity.com/paper/2105.00162/) (2021)
- [Shared Visual Representations of Drawing for Communication: How do different biases affect human interpretability and intent?](https://mlsanity.com/paper/2110.08203/) (2021)
- [The Image Reconstruction Game: Drawing Common Ground Through Iterative Multimodal Dialogue](https://mlsanity.com/paper/2606.01901/) (2026)

## Abstract (arXiv)

We attempt to automate various artistic processes by inventing a set of drawing games, analogous to the approach taken by emergent language research in inventing communication games. A critical difference is that drawing games demand much less effort from the receiver than do language games. Artists must work with pre-trained viewers who spend little time learning artist specific representational conventions, but who instead have a pre-trained visual system optimized for behaviour in the world by understanding to varying extents the environment's visual affordances. After considering various kinds of drawing game we present some preliminary experiments which have generated images by closing the generative-critical loop.