在不可预测的领域中为谈判团队提供一致可接受的协议
Unanimously acceptable agreements for negotiation teams in unpredictable domains
摘要：
谈判团队是一组具有共同偏好且可能相互冲突的代理人，形成谈判的一方。一个谈判团队同时参与两个决策过程，一个是与对手的谈判，另一个是决定谈判中行动的团队内部过程。这篇文章的重点是谈判团队决策的情况下，需要团队决策的一致性。现有的基于代理的方法只能保证团队在完全由可预测和兼容的问题组成的域中进行谈判的一致性。本文提出了一个模型，谈判团队，保证一致的团队决策域组成的可预测的和兼容的，也不可预测的问题。此外，本文还探讨了使用对手模型和团队成员模型对团队成员提出策略的影响。实验结果表明，如果团队成员采用贝叶斯学习来建模他们的队友的偏好，团队受益。
英文摘要：
A negotiation team is a set of agents with common and possibly also conflicting preferences that forms one of the parties of a negotiation. A negotiation team is involved in two decision making processes simultaneously, a negotiation with the opponents, and an intra-team process to decide on the moves to make in the negotiation. This article focuses on negotiation team decision making for circumstances that require unanimity of team decisions. Existing agent-based approaches only guarantee unanimity in teams negotiating in domains exclusively composed of predictable and compatible issues. This article presents a model for negotiation teams that guarantees unanimous team decisions in domains consisting of predictable and compatible, and also unpredictable issues. Moreover, the article explores the influence of using opponent, and team member models in the proposing strategies that team members use. Experimental results show that the team benefits if team members employ Bayesian learning to model their teammates' preferences.
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。
