Persuading Voters: It's Easy to Whisper, It's Hard to Speak Loud
Matteo Castiglioni, Andrea Celli, Nicola Gatti
摘要
We focus on the following natural question: is it possible to influence the outcome of a voting process through the strategic provision of information to voters who update their beliefs rationally? We investigate whether it is computationally tractable to design a signaling scheme maximizing the probability with which the sender's preferred candidate is elected. We resort to the model recently introduced by Arieli and Babichenko (2019) (i.e., without inter-agent externalities), and focus on, as illustrative examples, k-voting rules and plurality voting. There is a sharp contrast between the case in which private signals are allowed and the more restrictive setting in which only public signals are allowed. In the former, we show that an optimal signaling scheme can be computed efficiently both under a k-voting rule and plurality voting. In establishing these results, we provide two contributions applicable to general settings beyond voting. Specifically, we extend a well-known result by Dughmi and Xu (2017) to more general settings and prove that, when the sender's utility function is anonymous, computing an optimal signaling scheme is fixed-parameter tractable in the number of receivers' actions. In the public signaling case, we show that the sender's optimal expected return cannot be approximated to within any factor under a k-voting rule. This negative result easily extends to plurality voting and problems where utility functions are anonymous.
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引用它的顶会 Paper12
- Multi-Receiver Online Bayesian PersuasionMatteo Castiglioni, Alberto Marchesi, Andrea Celli, Nicola GattiICML 2021 · 被引用 36 次
- Bayesian Persuasion in Sequential Decision-MakingJiarui Gan, Rupak Majumdar, Goran Radanovic, Adish SinglaAAAI 2022 · 被引用 30 次
- Private Bayesian Persuasion with Sequential GamesAndrea Celli, Stefano Coniglio, Nicola GattiAAAI 2020 · 被引用 29 次
- Optimal Rates and Efficient Algorithms for Online Bayesian PersuasionMartino Bernasconi, Matteo Castiglioni, Andrea Celli, Alberto Marchesi 等ICML 2023 · 被引用 26 次
- Online Bayesian PersuasionMatteo Castiglioni, Andrea Celli, Alberto Marchesi, Nicola GattiNeurIPS 2020 · 被引用 26 次
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