# A Soft Inducement Framework for Incentive-Aided Steering of No-Regret Players

arXiv: https://arxiv.org/abs/2508.21672 · HTML: https://mlsanity.com/paper/2508.21672/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 30 references that are in the map.
- First posted on arXiv 29 Aug 2025.

## Builds on (most cited first, 4 of 4)

- [Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems](https://mlsanity.com/paper/1901.10923/) (2019)
- [Inducing Equilibria via Incentives: Simultaneous Design-and-Play Ensures Global Convergence](https://mlsanity.com/paper/2110.01212/) (2021)
- [Steering No-Regret Learners to a Desired Equilibrium](https://mlsanity.com/paper/2306.05221/) (2023)
- [Multi-Channel Bayesian Persuasion](https://mlsanity.com/paper/2111.09789/) (2021)

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

- [Meta-Learning for Repeated Bayesian Persuasion](https://mlsanity.com/paper/2603.20408/) (2026)

## Abstract (arXiv)

In this work, we investigate a steering problem in a mediator-augmented two-player normal-form game, where the mediator aims to guide players toward a specific action profile through information and incentive design. We first characterize the games for which successful steering is possible. Moreover, we establish that steering players to any desired action profile is not always achievable with information design alone, nor when accompanied with sublinear payment schemes. Consequently, we derive a lower bound on the constant payments required per round to achieve this goal. To address these limitations incurred with information design, we introduce an augmented approach that involves a one-shot information design phase before the start of the repeated game, transforming the prior interaction into a Stackelberg game. Finally, we theoretically demonstrate that this approach improves the convergence rate of players' action profiles to the target point by a constant factor with high probability, and support it with empirical results.