A Workshop on Information Aggregation in Decision Making, University of Maryland May 1-3, 2003

实际上，所有的决策都是在收集和组合信息之后做出的。这种被称为信息聚合的过程，无论它是一个个人、一个群体还是一个计算机算法做出决定，都会发生。例如，个人在选择癌症治疗、选择投资组合或购买房屋时，会从各种来源寻求信息，并在做出决定之前考虑要做出哪些权衡。群体也要经历同样的过程，但除此之外，还必须将成员的不同意见结合起来，以达成单一的群体决策。而用于现实世界决策的最优模型或高效算法，例如调度或分配资源，或基于不同检测器的输出做出选择，可以根据多个标准平衡多个资源需求。尽管在个人、群体和计算决策方面有形式上的相似之处，但这三个领域的研究人员很少相互交流。个人信息聚合、群体决策和优化领域之间相对缺乏联系的部分原因是，这些领域的传统研究是根据严格的学科界限进行的。本次研讨会的目的是促进跨领域的合作，以及思想、模型和方法的交流。它将通过汇集杰出的科学家来实现这些目标，这些科学家的研究重点是群体和个人决策中的信息聚合，或在运筹学、分布式检测、统计学和正式决策科学中的相关主题，以便各个调查领域可以从他们的相似之处受益，并从他们的差异中学习。本次研讨会以实证和理论贡献为基础，将对个人、群体和最优决策等重要领域的研究去区域化产生重大的积极影响。

Virtually all decisions are preceded by gathering and combining information. Such information aggregation, as this process is called, occurs regardless of whether it is an individual, a group, or a computer algorithm that is making the decision. For example, individuals choosing among cancer treatments, selecting investment portfolios, or purchasing homes seek information from various sources and consider what tradeoffs to make prior to arriving at their decisions. Groups go through the same process, but in addition, must combine the separate opinions of their members to arrive at a single group decision. And optimal models or efficient algorithms for real-world decisions, such as scheduling or allocating resources, or making a choice based on the outputs of distinct detectors, balance multiple resource demands against multiple criteria. Despite the formal similarities across individual, group, and computational decision making, researchers in the three areas rarely communicate with each other. Part of the reason for the relative lack of contact between the individual-information-aggregation, group-decision-making, and optimization areas is that traditionally research in these domains has been conducted according to strict disciplinarily lines. The purpose of this workshop is to foster cross-area collaboration, as well as exchange of ideas, models, and methods. It will accomplish these goals by bringing together eminent scientists whose research is focused on information aggregation in group and individual decision-making, or in associated topics in operations research, distributed detection, statistics, and formal decision science, so that the various areas of inquiry may benefit from their similarities and learn from their differences. This workshop, built around both empirical and theoretical contributions, will have a significant positive influence toward de-compartmentalizing the research in the important areas of individual, group, and optimal decision-making.