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20212023
most citedInverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality

6 citations · 28 across the 20 of their papers we have counts for

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15 papers · 1 filter

cs.GT2023

Markov Persuasion Processes with Endogenous Agent Beliefs

Krishnamurthy Iyer, Haifeng Xu, You Zu

We consider a dynamic Bayesian persuasion setting where a single long-lived sender persuades a stream of ``short-lived'' agents (receivers) by sharing information about a payoff-re…

cs.GT2023★ 4 cited

Rethinking Incentives in Recommender Systems: Are Monotone Rewards Always Beneficial?

Fan Yao, Chuanhao Li, Karthik Abinav Sankararaman +5

The past decade has witnessed the flourishing of a new profession as media content creators, who rely on revenue streams from online content recommendation platforms. The reward me…

cs.GT2023

Bayesian Calibrated Click-Through Auction

Junjie Chen, Minming Li, Haifeng Xu +1

We study information design in click-through auctions, in which the bidders/advertisers bid for winning an opportunity to show their ads but only pay for realized clicks. The payme…

cs.GT2023★ 1 cited

Robust Stackelberg Equilibria

Jiarui Gan, Minbiao Han, Jibang Wu +1

This paper provides a systematic study of the robust Stackelberg equilibrium (RSE), which naturally generalizes the widely adopted solution concept of the strong Stackelberg equili…

cs.GT2023★ 3 cited

How Bad is Top- Recommendation under Competing Content Creators?

Fan Yao, Chuanhao Li, Denis Nekipelov +2

Content creators compete for exposure on recommendation platforms, and such strategic behavior leads to a dynamic shift over the content distribution. However, how the creators' co…

cs.GT2022★ 6 cited

Inverse Game Theory for Stackelberg Games: the Blessing of Bounded Rationality

Jibang Wu, Weiran Shen, Fei Fang +1

Optimizing strategic decisions (a.k.a. computing equilibrium) is key to the success of many non-cooperative multi-agent applications. However, in many real-world situations, we may…

cs.GT2022

Information Design in the Principal-Agent Problem

Yakov Babichenko, Inbal Talgam-Cohen, Haifeng Xu +1

We study a variant of the principal-agent problem in which the principal does not directly observe the agent's effort outcome; rather, she gets a signal about the agent's action ac…

cs.GT2022★ 1 cited

Generalized Principal-Agency: Contracts, Information, Games and Beyond

Jiarui Gan, Minbiao Han, Jibang Wu +1

In the principal-agent problem formulated by Myerson'82, agents have private information (type) and make private decisions (action), both of which are unobservable to the principal…

cs.GT2022

No-Regret Bayesian Recommendation to Homogeneous Users

Yiding Feng, Wei Tang, Haifeng Xu

We introduce and study the online Bayesian recommendation problem for a recommender system platform. The platform has the privilege to privately observe a utility-relevant \emph{st…

cs.GT2021

Multi-Channel Bayesian Persuasion

Yakov Babichenko, Inbal Talgam-Cohen, Haifeng Xu +1

The celebrated Bayesian persuasion model considers strategic communication between an informed agent (the sender) and uninformed decision makers (the receivers). The current rapidl…

cs.GT2021

Uncoupled Bandit Learning towards Rationalizability: Benchmarks, Barriers, and Algorithms

Jibang Wu, Haifeng Xu, Fan Yao

Under the uncoupled learning setup, the last-iterate convergence guarantee towards Nash equilibrium is shown to be impossible in many games. This work studies the last-iterate conv…

cs.GT2021★ 1 cited

The Limits of Optimal Pricing in the Dark

Quinlan Dawkins, Minbiao Han, Haifeng Xu

A ubiquitous learning problem in today's digital market is, during repeated interactions between a seller and a buyer, how a seller can gradually learn optimal pricing decisions ba…

cs.GT2021

Algorithmic Information Design in Multi-Player Games: Possibility and Limits in Singleton Congestion

Chenghan Zhou, Thanh H. Nguyen, Haifeng Xu

Most algorithmic studies on multi-agent information design so far have focused on the restricted situation with no inter-agent externalities; a few exceptions investigated truly st…

cs.GT2021

Auctioning with Strategically Reticent Bidders

Jibang Wu, Ashwinkumar Badanidiyuru, Haifeng Xu

We propose and study a novel mechanism design setup where each bidder holds two kinds of private information: (1) type variable, which can be misreported; (2) information variable,…

cs.GT2021

Competitive Information Design for Pandora's Box

Bolin Ding, Yiding Feng, Chien-Ju Ho +2

We study a natural competitive-information-design strategic variant for the celebrated Pandora's Box problem (Weitzman, 1979), where each box is associated with a strategic informa…