# Oblivious Learning and Collusive Pricing

arXiv: https://arxiv.org/abs/2606.05363 · HTML: https://mlsanity.com/paper/2606.05363/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 70 references that are in the map.
- First posted on arXiv 3 Jun 2026.

## Builds on (most cited first, 7 of 7)

- [Algorithmic Collusion by Large Language Models](https://mlsanity.com/paper/2404.00806/) (2024)
- [Artificial Intelligence and Spontaneous Collusion](https://mlsanity.com/paper/2202.05946/) (2022)
- [Algorithmic Collusion Without Threats](https://mlsanity.com/paper/2409.03956/) (2024)
- [Supracompetitive Pricing Under AI Monoculture](https://mlsanity.com/paper/2601.01279/) (2026)
- [Conjectural Variations in Competitive Dynamic Pricing: A Learning Foundation via Experimentation Design and Feedback Structure](https://mlsanity.com/paper/2602.12888/) (2026)
- [Online Price Competition under Generalized Linear Demands](https://mlsanity.com/paper/2511.10718/) (2025)
- [Misspecified Estimate-then-Optimize Leads to Supra-Competitive Prices](https://mlsanity.com/paper/2605.16064/) (2026)

## Built on by (most cited first, 1 of 1)

- [Persistent Partners Raise Prices Among Learning Agents](https://mlsanity.com/paper/2609.35402/) (2026)

## Abstract (arXiv)

On a platform with many sellers, should a pricing algorithm explicitly model competitors' prices when learning demand? Classical arguments suggest that ignoring competitors induces model misspecification and inefficiency, yet findings from algorithmic collusion suggest that ignoring competitor prices may, surprisingly, facilitate collusive outcomes and improve profits. We study this problem in a competitive market with unknown noisy demand, in which sellers repeatedly set prices, either incorporating competitor prices in learning their demand models (informed), or ignoring them (oblivious). We show that, relative to a monopolist, an oblivious seller in a competitive market must conduct more aggressive price exploration to compensate for the loss of dynamic competitor information. When all sellers are oblivious, prices converge to the competitive outcome under persistent exploration, while a continuum of pseudo-equilibria arises when exploration is "insufficient." In markets with a mix of oblivious and informed sellers, the informed strictly out-earn the oblivious. In game-theoretic terms, the unique Nash equilibrium is the all-informed market, in which prices converge to the competitive outcome efficiently, and oblivious modeling does not robustly lead to collusive patterns.