摘要翻译：
研究了自利自治Agent之间的双边多问题协商问题。现在，有许多不同的程序可用于这一过程；三个主要的程序是：一揽子处理程序，将所有问题捆绑在一起讨论；同时处理程序，将问题同时但相互独立地讨论；顺序处理程序，将问题一个接一个地讨论。由于每一个都产生不同的结果，一个关键问题是决定在哪些情况下使用哪一个。具体地说，我们考虑了一个模型，在这个模型中，代理具有时间约束（以最后期限和折扣因子的形式）和信息不确定性（代理不知道对手的效用函数）。对于该模型，我们考虑了既独立又相互依赖的问题，并为每个过程确定了每个情况的平衡。这样，我们就表明一揽子交易实际上是对各方最优的程序。然后我们接着说明，尽管一揽子交易在计算上可能比其他两种程序复杂，但它产生帕累托最优结果（与其他两种程序不同），它具有与同时进行的程序（比顺序进行的程序更好）相似的最早和最晚可能的一致时间，而且它（与其他两种程序一样）只有在某些条件下（我们定义的）才产生唯一的结果。
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英文标题：
《Multi-Issue Negotiation with Deadlines》
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作者：
S. S. Fatima, N. R. Jennings, M. J. Wooldridge
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最新提交年份：
2011
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Multiagent Systems        多智能体系统
分类描述：Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
涵盖多Agent系统、分布式人工智能、智能Agent、协调交互。和实际应用。大致涵盖ACM科目I.2.11类。
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一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  This paper studies bilateral multi-issue negotiation between self-interested autonomous agents. Now, there are a number of different procedures that can be used for this process; the three main ones being the package deal procedure in which all the issues are bundled and discussed together, the simultaneous procedure in which the issues are discussed simultaneously but independently of each other, and the sequential procedure in which the issues are discussed one after another. Since each of them yields a different outcome, a key problem is to decide which one to use in which circumstances. Specifically, we consider this question for a model in which the agents have time constraints (in the form of both deadlines and discount factors) and information uncertainty (in that the agents do not know the opponents utility function). For this model, we consider issues that are both independent and those that are interdependent and determine equilibria for each case for each procedure. In so doing, we show that the package deal is in fact the optimal procedure for each party. We then go on to show that, although the package deal may be computationally more complex than the other two procedures, it generates Pareto optimal outcomes (unlike the other two), it has similar earliest and latest possible times of agreement to the simultaneous procedure (which is better than the sequential procedure), and that it (like the other two procedures) generates a unique outcome only under certain conditions (which we define).
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PDF链接：
https://arxiv.org/pdf/1110.2765