# Equilibria in multiagent online problems with predictions

arXiv: https://arxiv.org/abs/2405.11873 · HTML: https://mlsanity.com/paper/2405.11873/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 May 2024.

## Built on by (most cited first, 2 of 2)

- [Competitive Algorithms for Multi-Agent Ski-Rental Problems](https://mlsanity.com/paper/2507.15727/) (2025)
- [Analyzing the effect of prediction accuracy on the distributionally-robust competitive ratio](https://mlsanity.com/paper/2601.06813/) (2026)

## Abstract (arXiv)

We study the power of (competitive) algorithms with predictions in a multiagent setting. To this goal, we introduce a multiagent version of the ski-rental problem. In this problem agents can collaborate by pooling resources to get a group license for some asset. If the license price is not met then agents have to rent the asset individually for the day at a unit price. Otherwise the license becomes available forever to everyone at no extra cost. We investigate the effect of using predictors for self and others' behavior in such a setting, as well as the new equilibria formed in this way.