Zobrazeno 1 - 10
of 2 196
pro vyhledávání: '"Bayesian persuasion"'
Autor:
Bacchiocchi, Francesco, Bollini, Matteo, Castiglioni, Matteo, Marchesi, Alberto, Gatti, Nicola
We study online Bayesian persuasion problems in which an informed sender repeatedly faces a receiver with the goal of influencing their behavior through the provision of payoff-relevant information. Previous works assume that the sender has knowledge
Externí odkaz:
http://arxiv.org/abs/2411.06141
We study a Bayesian persuasion problem with externalities. In this model, a principal sends signals to inform multiple agents about the state of the world. Simultaneously, due to the existence of externalities in the agents' utilities, the principal
Externí odkaz:
http://arxiv.org/abs/2412.12859
We introduce the concept of leakage-robust Bayesian persuasion. Situated between public persuasion [KG11, CCG23, Xu20] and private persuasion [AB19], leakage-robust persuasion considers a setting where one or more signals privately sent by a sender t
Externí odkaz:
http://arxiv.org/abs/2411.16624
We address the fundamental problem of selection under uncertainty by modeling it from the perspective of Bayesian persuasion. In our model, a decision maker with imperfect information always selects the option with the highest expected value. We seek
Externí odkaz:
http://arxiv.org/abs/2410.11798
Autor:
Li, Xinyu
This paper explores how ad platforms can utilize Bayesian persuasion within blockchain-based auction systems to strategically influence advertiser behavior despite increased transparency. By integrating game-theoretic models with machine learning tec
Externí odkaz:
http://arxiv.org/abs/2410.07392
Autor:
Deori, Reema, Kulkarni, Ankur A.
A persuasion policy successfully persuades an agent to pick a particular action only if the information is designed in a manner that convinces the agent that it is in their best interest to pick that action. Thus, it is natural to ask, what makes the
Externí odkaz:
http://arxiv.org/abs/2408.13822
We consider a susceptible-infected-susceptible (SIS) epidemic model in which a large group of individuals decide whether to adopt partially effective protection without being aware of their individual infection status. Each individual receives a sign
Externí odkaz:
http://arxiv.org/abs/2410.20303
Autor:
Bai, Fengshuo, Wang, Mingzhi, Zhang, Zhaowei, Chen, Boyuan, Xu, Yinda, Wen, Ying, Yang, Yaodong
With recent advancements in large language models (LLMs), alignment has emerged as an effective technique for keeping LLMs consensus with human intent. Current methods primarily involve direct training through Supervised Fine-tuning (SFT) or Reinforc
Externí odkaz:
http://arxiv.org/abs/2405.18718