activity
20122026
most citedAn Overview of Machine Teaching

102 citations · 609 across the 64 of their papers we have counts for

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Showing cs.GTShow all

8 papers · 1 filter

cs.GT2026

The Game Changer Problem: Controlling Equilibria with Discrete Rewards

Brandon Han, Young Wu, Shiyun Cheng +1

We introduce the game changer problem, where an external designer modifies a game's reward matrix to make a target pure action profile the unique equilibrium, subject to the constr…

cs.GT2026

Pure Nash Equilibria under the Affine Mechanism: A Potential Game of Exaggeration

Jason Jisen Li, Young Wu, Yancheng Zhu +2

The mean mechanism is known to be non-incentive-compatible, namely, rational players are incentivized to misreport their values. Despite this game-theoretic issue, the mean mechani…

cs.GT2025

Optimally Installing Strict Equilibria

Jeremy McMahan, Young Wu, Yudong Chen +2

In this work, we develop a reward design framework for installing a desired behavior as a strict equilibrium across standard solution concepts: dominant strategy equilibrium, Nash…

cs.GT2025

The Battling Influencers Game: Nash Equilibria Structure of a Potential Game and Implications to Value Alignment

Young Wu, Yancheng Zhu, Jin-Yi Cai +1

When multiple influencers attempt to compete for a receiver's attention, their influencing strategies must account for the presence of one another. We introduce the Battling Influe…

cs.GT2023

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value

Young Wu, Jeremy McMahan, Yiding Chen +3

We study the game modification problem, where a benevolent game designer or a malevolent adversary modifies the reward function of a zero-sum Markov game so that a target determini…

cs.GT2023

VISER: A Tractable Solution Concept for Games with Information Asymmetry

Jeremy McMahan, Young Wu, Yudong Chen +2

Many real-world games suffer from information asymmetry: one player is only aware of their own payoffs while the other player has the full game information. Examples include the cr…

cs.GT2023

Mechanism Design for Collaborative Normal Mean Estimation

Yiding Chen, Xiaojin Zhu, Kirthevasan Kandasamy

We study collaborative normal mean estimation, where strategic agents collect i.i.d samples from a normal distribution at a cost. They all wish to estimat…

cs.GT2021★ 2 cited

Game Redesign in No-regret Game Playing

Yuzhe Ma, Young Wu, Xiaojin Zhu

We study the game redesign problem in which an external designer has the ability to change the payoff function in each round, but incurs a design cost for deviating from the origin…