好奇心意识讨价还价
Curiosity-Aware Bargaining
摘要：
对手建模包括对代理的策略或偏好进行建模，这要归功于它提供的数据。在自动化谈判和机器学习的背景下，它可以产生压倒性的优势，以至于它可能会限制一些临时代理成为谈判过程的一部分。我们有资格作为“好奇”的代理人的谈判的愿望，以收集信息和改善其对手的模型驱动。然而，在自动协商中，基于好奇心的理性协议和好奇心-鲁棒协议还没有被研究。在本文中，我们依靠机制设计提出了三个扩展的标准讨价还价协议，限制信息泄漏。这些扩展是由一个增强的合理性模型，认为交换信息的支持。并对它们进行了理论分析和实验评价。
英文摘要：
Opponent modeling consists in modeling the strategy or preferences of an agent thanks to the data it provides. In the context of automated negotiation and with machine learning, it can result in an advantage so overwhelming that it may restrain some casual agents to be part of the bargaining process. We qualify as "curious" an agent driven by the desire of negotiating in order to collect information and improve its opponent model. However, neither curiosity-based rational-ity nor curiosity-robust protocol have been studied in automatic negotiation. In this paper, we rely on mechanism design to propose three extensions of the standard bargaining protocol that limit information leak. Those extensions are supported by an enhanced rationality model, that considers the exchanged information. Also, they are theoretically analyzed and experimentally evaluated.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
