Collaborative Research: Pilot Research on Language-Based Strategies for Creative Problem Solving

协作研究：基于语言的创造性问题解决策略的试点研究

• 批准号: 0757490
• 负责人: Michael Littman
• 金额: $ 10万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0757490&HistoricalAwards=false
• 关键词: Collaborative; Research; Pilot; Language; Based

When people reformulate a problem space, previously unseen structure emerges. This process can be decomposed into two steps: People must first recognize and then exploit novel structure. We suggest that both of these steps can be improved by experienced application of creative nominalization. Here, nominalization refers to the process of recognizing a novel concept and naming it appropriately. This project demonstrates that experience in nominalization can improve problem solving and that successful training and experience on nominalization has the potential to enhance people?s intrinsic motivation, and thereby effectiveness, with respect to creative aspects of problem solving. In parallel, the project explores the potential for nominalization as a strategy to enhance machine-learning agents in reinforcement learning environments. Inspired by research on animal learning, reinforcement learning is a branch of artificial intelligence research concerned with creating motivated, learning agents. In the reinforcement-learning setting, nominalization has the potential to create a first-class object, something that can be directly manipulated, recorded, analyzed, and composed with other objects to form higher-order structures. In addition, reinforcement-learning researchers have recently begun to consider how learning might be enhanced with intrinsic motivation to explore problem spaces. Thus nominalization can function in reinforcement-learning settings both as a direct strategy and indirectly via intrinsic motivation. The most significant broader impact of this project will be to provide a new intervention that will enhance the creativity and efficacy of problem solvers working alone or in collaborative groups. If successful, the relative simplicity of the intervention and its general applicability would make it a prime candidate for wide dispersal to people in disparate walks of like.

当人们重新准备一个问题空间时，以前看不见的结构就会出现。这个过程可以分解为两个步骤：人们必须首先识别然后利用新颖的结构。我们建议通过经验丰富的创意名义化可以改善这两个步骤。在这里，名义化是指识别新颖概念并适当命名的过程。该项目表明，名义化的经验可以改善解决问题的解决，而成功的术语培训和经验有可能增强人们的内在动机，从而在解决问题的创造性方面方面有效。同时，该项目探讨了名义化作为增强机器学习剂在增强学习环境中的策略的潜力。受动物学习研究的启发，强化学习是人工智能研究的一个分支，涉及创建动机的学习代理。在强化学习环境中，名义化具有创建一流对象的潜力，即可以直接操纵，记录，分析和与其他对象组成的东西形成高阶结构。此外，加强学习研究人员最近开始考虑如何通过探索问题空间的内在动机来增强学习。因此，名义化可以在加强学习环境中作为一种直接的策略，并通过内在动机间接发挥作用。该项目最重要的更广泛的影响是提供一种新的干预措施，以提高问题解决者单独工作或在协作小组中工作的创造力和功效。如果成功的话，干预的相对简单性及其一般适用性将使它成为散布在不同之类的人中的广泛散布的主要候选人。