Optimal Private Payoff Manipulation against Commitment in Extensive-form Games
Not on the map. Why?
Abstract (arXiv)
To take advantage of strategy commitment, a useful tactic of playing games, a leader must learn enough information about the follower's payoff function. However, this leaves the follower a chance to provide fake information and influence the final game outcome. Through a carefully contrived payoff function misreported to the learning leader, the follower may induce an outcome that benefits him more, compared to the ones when he truthfully behaves. We study the follower's optimal manipulation via such strategic behaviors in extensive-form games. Followers' different attitudes are taken into account. An optimistic follower maximizes his true utility among all game outcomes that can be induced by some payoff function. A pessimistic follower only considers misreporting payoff functions that induce a unique game outcome. For all the settings considered in this paper, we characterize all the possible game outcomes that can be induced successfully. We show that it is polynomial-time tractable for the follower to find the optimal way of misreporting his private payoff information. Our work completely resolves this follower's optimal manipulation problem on an extensive-form game tree.
Key facts. Cited by 2 papers in the map (data through 13 Oct 2026). Builds on 8 of its 45 references that are in the map. First posted on arXiv 27 Jun 2022.
Builds on
8 of 45 references.
References · 8
- 2020Dynamic Incentive-aware Learning: Robust Pricing in Contextual Auctionscited by 34
- 2015Watch and Learn: Optimizing from Revealed Preferences Feedbackcited by 17
- 2020Optimally Deceiving a Learning Leader in Stackelberg Gamescited by 11
- 2019Imitative Follower Deception in Stackelberg Gamescited by 9
- 2019Manipulating a Learning Defender and Ways to Counteractcited by 8
- 2015Computation of Stackelberg Equilibria of Finite Sequential Gamescited by 4
- 2022Budget-Constrained Auctions with Unassured Priors: Strategic Equivalence and Structural Propertiescited by 2
- 2019Stackelberg Punishment and Bully-Proofing Autonomous Vehiclescited by 1
Built on by
Citing papers per year: 2024: 2.
2 papers.