# A Rational Account of Categorization Based on Information Theory

arXiv: https://arxiv.org/abs/2603.29895 · HTML: https://mlsanity.com/paper/2603.29895/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 16 references that are in the map.
- First posted on arXiv 7 Feb 2026.

## Builds on (most cited first, 1 of 1)

- [Cobweb: An Incremental and Hierarchical Model of Human-Like Category Learning](https://mlsanity.com/paper/2403.03835/) (2024)

## Abstract (arXiv)

We present a new theory of categorization based on an information-theoretic rational analysis. To evaluate this theory, we investigate how well it can account for key findings from classic categorization experiments conducted by Hayes-Roth and Hayes-Roth (1977), Medin and Schaffer (1978), and Smith and Minda (1998). We find that it explains the human categorization behavior as well as (or better) than the independent cue and context models (Medin & Schaffer, 1978), the rational model of categorization (Anderson, 1991), and a hierarchical Dirichlet process model (Griffiths et al., 2007).