RI: Small: New Directions in Computational Social Choice and Mechanism Design

我们经常需要做出集体决定：谁将代表我们担任主席，我们今晚将在哪里出去吃饭，谁将接受奖励，等等。人工智能中的多智能体系统也面临着类似的问题。做出这种决定的最佳程序是什么？代理人可以对结果进行投票，但具体的程序应该是什么呢？这在社会选择理论和机制设计理论中得到了研究，后者特别关注那些出于自身利益而采取战略行动的主体。然而，越来越多的活动转移到网上，集体决策也不例外。例如，我们对在线内容、产品和人物进行评级或投票。这些新应用的关键方面不存在于传统的社会选择和机制设计模型中。例如，在基于互联网的机制中，谁可以访问，谁将参与？我们怎么知道一个行为人没有参与多次呢？当投票事件的数量可能势不可挡时，我们如何允许代理人有意义地参与？建议的研究旨在扩展传统模型，以纳入这些方面，并开发新的算法和其他技术，以确保结果有意义，提高经济效率和人类福利。在许多领域中，多个自利益主体需要做出集体决策。社会选择理论关注的是如何做出这样的集体决策。与此密切相关的是，机制设计理论关注的是如何设计机制来解决这样的问题，即使在代理人采取战略行动的情况下也能产生良好的结果。近年来，在理解社会选择和机制设计的计算方面取得了重大进展。在提议的研究中，PI和他的团队着手将这些技术应用于新的领域，比如那些由互联网或新数据可用性支持的领域。例如，一个关键问题是参与代理的身份。在一个以互联网为基础的机制中，谁能进入，谁将参与？我们怎么知道一个行为人没有参与多次呢？PI和他的团队的目标是用基于社会网络结构的技术来解决这些问题，以及基于代理参与所付出的努力。另一个关键问题是代理策略性地提供不准确数据的可能性。同样，对代理人的努力成本进行显式建模将发挥关键作用。

We often need to make collective decisions: who will represent us as president, where will we all go out for dinner tonight, who will receive the award, and so on. Similar problems are faced in multiagent systems in artificial intelligence. What are the best procedures for reaching such decisions? The agents could vote over the outcome, but what should the exact procedure be? This is studied in the theories of social choice and mechanism design, with the latter focusing particularly on agents that act strategically in their own self-interest. However, an ever-increasing amount of activity is moving online, and collective decision making is no exception. For example, we rate or vote on content, products, and people online. Key aspects of these novel applications are not present in the traditional models of social choice and mechanism design. For example, in an Internet-based mechanism, who gets to and who will participate? How can we know that a single agent is not participating multiple times? How can we allow agents to meaningfully participate when the number of voting events is potentially overwhelming? The proposed research aims to extend the traditional models to incorporate these aspects and to develop new algorithmic and other techniques to ensure outcomes are meaningful and increase economic efficiency and human welfare.In many domains, multiple self-interested agents need to make a collective decision. The theory of social choice concerns how such collective decisions should be made. Closely related, the theory of mechanism design concerns how to design mechanisms for such problems that result in good outcomes even when agents behave strategically. In recent years, major progress has been made on understanding the computational aspects of both social choice and mechanism design. In the proposed research, the PI and his team set out to adapt these techniques to novel domains such as those enabled by the Internet or the availability of new data. For example, one key issue is the identity of the participating agents. In an Internet-based mechanism, who gets to and who will participate? How can we know that a single agent is not participating multiple times? The PI and his team aim to address such issues with techniques based on social network structure, as well as on the effort that agents expend participating. Another key issue is the possibility of agents strategically providing inaccurate data. Again, explicit modeling of the agents' effort costs in doing so will play a key role.