Collaborative Research: Determining the Fundamental Cognitive Properties of Decision Making

项目的非技术描述在一个人做出的几乎每一个决定中，他们都需要结合多个，有时是相互冲突的来源信息。因此，了解人们如何使用这些多种信息来源是理解和预测选择的基础。心理学中已建立的方法允许在某些情况下检查这些过程。例如，为了探索决策阶段，可能会要求决策者在做出选择时描述她的思维过程，并且该描述用于告知研究人员。在许多情况下，关于选择过程的直接信息是无法获得的。例如，决策者可能会搜索她的记忆，以找到可用于在选项之间做出选择的信息。当记忆搜索速度很快时，人们很少能清楚地了解记忆是如何被访问和使用的。为了在最广泛的情况下调查基于多种信息来源的决策，主要研究人员将整合基于数学认知模型和标准决策研究方法的强大方法。本研究将实现三个目标：(1)对决策过程中多种信息来源的组合有一个重要的认识；(2)对不同决策任务的基本过程进行新的实证检验；(3)在新的实证发现的基础上严格比较顶级决策理论。这些结果将为决策者提供信息，评估决策效率，并建立更好的选择行为模型。技术描述多年来，提出了几个决策模型，可以解释人类决策中的许多典型发现，使用选择准确性和响应时间输出度量。然而，关于潜在的认知机制尚未达成明确的共识。这些模型通常可以通过对导致决策的过程的强烈暗示来区分。具体来说，这些模型暗示了(a)如何搜索信息，(b)何时停止信息搜索，以及(c)如何整合获取的信息以达成决策。尽管如此，分歧依然存在。在某种程度上，这是由于模型模仿：没有适当的实验设计和分析，不同的理论可以做出相同的预测。例如，基于传统平均响应时间（RT）分析的推断由于模型模仿而受到限制，因为不同的决策模型可能意味着完全相同的平均响应时间模式。为了克服这一限制，我们将强大的系统析因技术（SFT）与传统的决策方法相结合。SFT已经成功地应用于广泛的感知和认知任务中，以识别加工顺序、停止规则和过程依赖性（上文的a、b和c），但仅以非常有限的方式应用于决策。我们的研究将把SFT与经典的判断和决策方法联系起来，以提高我们对决策背后的认知过程的理解。我们的项目还将有助于提高两所州立大学本科生和研究生的专业学术发展，这两所大学传统上对学生的研究机会较少。该研究项目的所有方面，从方法论到理论发展，将在国内和国际专业领域进行交流。此外，该研究将提交给高质量的同行评审期刊。拟议研究的目的之一是通过我们各自的大学新闻办公室向更广泛的受众传播研究结果。该奖项反映了美国国家科学基金会的法定使命，并通过基金会的知识价值和更广泛的影响审查标准进行了评估，认为值得支持。

Non-technical Description of the ProjectIn nearly every decision a person makes, they are required to combine multiple, sometimes conflicting sources information. Thus, understanding how people use these multiple sources of information is fundamental to understanding and predicting choices. Established approaches within psychology allow examination these processes in some situations. For example, to explore decision stages, a decision-maker may be asked to describe her thought process when making a choice, and that description is used to inform the researcher. In many situations, direct information about the choice processes is not accessible. For example, a decision maker may search her memory to find the information that could be used for choosing between options. When memory search is fast, people rarely have clear insight into how the memories were accessed and used. To allow for investigating decisions based on multiple sources of information across the widest range of situations, the principal investigators will integrate a powerful methodology based on mathematical cognitive modelling with standard decision-making research methodologies. The research will accomplish three objectives: (1) to gain an important understanding how multiple sources of information are combined during decision making, (2) conduct new empirical tests of the fundamental process across different decision making tasks, and (3) rigorously compare among the top decision making theories based on the new empirical findings. These results will inform decision makers, allow assessment of decision making efficiency, and enable better models of choice behavior.Technical DescriptionOver the years, several decision making models were proposed that can account for many of the typical findings in human decision making, using both choice accuracy and response time output measures. However, no clear agreement about the underlying cognitive mechanism has been reached. These models can often be distinguished by strong implications about the processes that lead to a decision. Specifically, these models imply (a) how information is searched for, (b) when this information search is stopped, and (c) how the acquired information is integrated to reach the decision. Nonetheless, the disagreement remains. In part this is due to model mimicking: Without appropriate experimental design and analysis, different theories can make equivalent predictions. For example, inferences based on traditional mean response time (RT) analysis are limited due to model mimicking, as different decision-making models can imply exactly the same mean response time patterns. To overcome this limitation, we will integrate the powerful systems factorial technology (SFT) with traditional decision-making methods. SFT has been successfully applied in a wide range of perceptual and cognitive tasks to identify processing order, stopping rule and process dependency (a, b, and c from above), but has only been applied to decision making in very limited way. Our research will link SFT to the classical methods in judgment and decision making to improve our understanding of the cognitive processes underlying decision-making. Our project will also contribute to improving the professional academic development of undergraduate and graduate students at two state universities that traditionally have fewer research opportunities for students. All aspects of this research project, from methodology to theoretical development, will be communicated at national and international professional Furthermore, the research will be submitted for publication in high-quality, peer-reviewed journals. One of the aims of the proposed research is to disseminate the findings to a broader audience through our respective university press officesThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.