Causal Discovery Workbench and Challenge Program

摘要提案编号：0725746提案标题：因果发现工作台和挑战项目名称：Guyon， Isabelle m.p pi机构：clopinet本研究的目的是设计一个虚拟实验室环境，使计算智能领域的研究人员能够提出和研究因果发现的新方法，即因果归因问题。因果发现对于医学、流行病学、生态学和经济等领域的科学发现和决策至关重要。协助政策制定的需要和大量数据的可用性对设计有效的方法以自动发现因果关系提出了新的要求。方法是首先围绕一些真实的和半人工的任务组织挑战，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，促进人工系统的虚拟实验。智力价值：促进科学进步需要标准基准，但是设计一个良好的因果发现基准平台，而不是偏向于特定的模型或方法，这不是微不足道的。两个关键因素区分了这个提议：(1)平台的交互方面，允许研究人员通过在系统上放置查询来模拟实验；(2)平台作为新问题和建议解决方案的存储库的动态方面。更广泛的影响：在互联网上开放参与的挑战，为任何出身的研究人员提供了一个很好的机会来展示他们的卓越，并迅速让他们知道自己。推进可靠地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。因果发现这门课对培养学生的科学发现逻辑具有特殊的教学意义。

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.