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From Shared Evidence to Group Attitudes

从共享证据到群体态度

基本信息

批准号：
282669151
负责人：
Professor Dr. Olivier Roy
金额：
--
依托单位：
Institute of Computer Sciences
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2016
资助国家：
德国
起止时间：
2015-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/282669151?language=en
关键词：
Shared Evidence Group Attitudes

项目摘要

Complex, coordinated efforts such as organizing national intelligence, rescuing flood victims, or conducting large-scale scientific research require both pooling and sharing information. These two processes are related but different. A commanding officer may pool intelligence and be able to locate a target while an agent in the field is unable to do so. The fact that the intelligence is not shared, or 'out in the open' for all field officers, might even be crucial to the success of the operation. What is, then, the precise relationship between pooling and sharing information? Is shared information always pooled? How can individuals with limited time and resources effectively share and/or pool the information they have? These questions have attracted a lot of attention in philosophical logic, but up to now the answers rest heavily on idealizations. Agents in these models are 'logically omniscient', i.e, they know all the logical consequences of their information. So in these models pooling is just a matter of putting together all the information of each agent. But in general reaching the right conclusions from pooling might not be trivial at all. Standard logical models also assume that the agents can store highly complicated notions, for instance an unbounded number of iterations of 'everybody knows that everybody knows that...', which are at the heart of the definition of so-called 'common knowledge.' This project will lift these idealizations and study sharing and pooling for agents with limited cognitive and inferential capacities. We will develop notions of shared information, e.g. common knowledge, for agents who do not have the full deductive power of classical models, and will use tools from the theory of judgment aggregation and belief merging to develop new logical models of information pooling for non-ideal agents. Finally, we will study how information dynamics in groups, and in particular the dialectics of questions and answers, can foster or prevent both pooling and sharing. The project will build on the work of an existing and rather successful Czech-German team of philosophical logicians. The team has been working on plausible models of the dynamics of knowledge and beliefs for resource-bounded individuals for some years now. The proposed research, focused on group information, is a natural next step.

组织国家情报、救援洪水灾民或开展大规模科学研究等复杂的协调工作需要汇集和共享信息。这两个过程既有联系又有区别。指挥官可以汇集情报，并能够定位目标，而在外地的代理人无法做到这一点。事实上，情报不共享，或“公开”给所有外勤人员，甚至可能是行动成功的关键。那么，汇集和共享信息之间的确切关系是什么？共享信息是否始终共享？时间和资源有限的个人如何有效地共享和/或汇集他们所拥有的信息？这些问题在哲学逻辑中引起了很多关注，但迄今为止，答案主要依赖于理想化。在这些模型中的代理人是“逻辑上全知的”，也就是说，他们知道他们的信息的所有逻辑后果。因此，在这些模型中，池化只是将每个代理的所有信息放在一起的问题。但总的来说，从池化中得出正确的结论可能并不是微不足道的。标准的逻辑模型还假设智能体可以存储高度复杂的概念，例如“每个人都知道每个人都知道……”的无限次迭代。”，这是所谓“常识”定义的核心。“这个项目将解除这些理想化，并研究认知和推理能力有限的代理人的共享和共享。我们将开发共享信息的概念，例如，共同的知识，对于那些没有经典模型的全部演绎能力的代理，并将使用判断聚合和信念合并理论的工具来开发非理想代理的信息池的新逻辑模型。最后，我们将研究群体中的信息动态，特别是问题和答案的辩证法，如何促进或阻止汇集和共享。该项目将建立在现有的相当成功的捷克-德国哲学逻辑学家团队的工作基础上。该团队多年来一直致力于为资源有限的个体研究知识和信念动态的合理模型。拟议中的研究，集中在群体信息，是一个自然的下一步。