Causal Discovery Workbench and Challenge Program

摘要提案编号：0725746提案标题：因果关系发现和挑战计划PI姓名： Guyon，Isabelle M.PI机构：Clopinet本研究的目的是设计一个虚拟实验室环境，使计算智能的研究人员能够提出和研究因果发现的新方法，即将原因归因于结果的问题。因果发现对于医学、流行病学、生态学和经济学等不同领域的科学发现和决策至关重要。辅助决策的需要和大量数据的可用性对设计有效的方法来自动化因果发现提出了新的要求。该方法是首先围绕一些或真实的和半人工任务组织一个挑战，以完善评估指标，然后设计和实现一个交互式的基于Web的环境，促进虚拟实验的人工systems.Intellectual优点：标准的基准需要促进科学进步，但一个良好的因果发现基准平台的设计，而不是偏向于某一特定的模型或方法，是不平凡的。这一提议有两个关键要素：（1）平台的互动性，使研究人员能够通过在系统上提出查询来模拟实验;（2）平台的动态性，作为新问题和拟议解决方案的储存库。通过互联网开放参与的挑战，为任何出身的研究人员提供了一个展示卓越并迅速使自己知名的好机会。推进可靠确定因果关系的方法将产生巨大的社会经济影响，例如通过改善政策制定。因果发现的主题是特别教学，以发展学生的科学发现的逻辑。

AbstractProposal Number: 0725746Proposal Title: Causal Discovery Workbench and Challenge ProgramPI Name: Guyon, Isabelle M.PI Institution: ClopinetThe objective of this research is to devise a virtual laboratory environment to enable researchers in computational intelligence to propose and study new methods of causal discovery, the problem of attributing causes to effects. Causal discovery is essential to scientific discovery and decision making in domains as diverse as medicine, epidemiology, ecology, and economy. The need for assisting policy making and the availability of massive amounts of data puts new requirements on the design of effective methods to automate causal discovery. The approach is to first organize a challenge around a number or real and semi-artificial tasks to refine evaluation metrics, then design and implement an interactive web-based environment facilitating virtual experiments on artificial systems.Intellectual merit: Standard benchmarks are needed to foster scientific progress, but the design of a good causal discovery benchmark platform, not biased in favor a particular model or approach, is not trivial. Two key elements distinguish this proposal: (1) the interactive aspect of the platform allowing researchers to emulate experimentation by placing queries on the systems; (2) the dynamic aspect of the platform acting as a repository of new problems and proposed solutions.Broader impact: Challenges with open participation over the Internet, provide a good opportunity for researchers of any origin to demonstrate excellence and quickly make themselves known. Advancing the methodology for reliably determining causal relationships would have a great socio-economical impact, e.g. by improving policy making. The subject of causal discovery is particularly pedagogical to develop the logic of scientific discovery in students.