# The Economics of No-regret Learning Algorithms

arXiv: https://arxiv.org/abs/2601.22079 · HTML: https://mlsanity.com/paper/2601.22079/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jan 2026.

## Built on by (most cited first, 3 of 3)

- [Bandit Allocational Instability](https://mlsanity.com/paper/2602.07472/) (2026)
- [Algorithmic Collusion and the Complexity of Information-Value-Free Equilibria](https://mlsanity.com/paper/2609.22757/) (2026)
- [Price of Anarchy of First-Price Auctions in Agentic Markets](https://mlsanity.com/paper/2610.20587/) (2026)

## Abstract (arXiv)

A fundamental challenge for modern economics is to understand what happens when actors in an economy are replaced with algorithms. Like rationality has enabled understanding of outcomes of classical economic actors, no-regret can enable the understanding of outcomes of algorithmic actors. This review article covers the classical computer science literature on no-regret algorithms to provide a foundation for an overview of the latest economics research on no-regret algorithms, focusing on the emerging topics of manipulation, statistical inference, and algorithmic collusion.