# Nash and Wardrop equilibria in aggregative games with coupling constraints

arXiv: https://arxiv.org/abs/1702.08789 · HTML: https://mlsanity.com/paper/1702.08789/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Feb 2017.

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

- [Stochastic Saddle Point Problems with Decision-Dependent Distributions](https://mlsanity.com/paper/2201.02313/) (2022)
- [Training Generalizable Collaborative Agents via Strategic Risk Aversion](https://mlsanity.com/paper/2602.21515/) (2026)
- [Convergence and Connectivity: Dynamics of Multi-Agent Q-Learning in Random Networks](https://mlsanity.com/paper/2503.10186/) (2025)

## Abstract (arXiv)

We consider the framework of aggregative games, in which the cost function of each agent depends on his own strategy and on the average population strategy. As first contribution, we investigate the relations between the concepts of Nash and Wardrop equilibrium. By exploiting a characterization of the two equilibria as solutions of variational inequalities, we bound their distance with a decreasing function of the population size. As second contribution, we propose two decentralized algorithms that converge to such equilibria and are capable of coping with constraints coupling the strategies of different agents. Finally, we study the applications of charging of electric vehicles and of route choice on a road network.