Workshop on Human Problem Solving: Difficult Optimization Problems, Indiana June 2005

人类问题解决研讨会：困难的优化问题，印第安纳州，2005 年 6 月

• 批准号: 0456651
• 负责人: Zygmunt Pizlo
• 金额: $ 1.43万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-15 至 2006-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0456651&HistoricalAwards=false
• 关键词: Workshop; Human; Problem; Solving; Difficult

During the last several years, there has been growing interest in studying how humans solve difficult optimization problems. The common feature of these tasks is an enormous search space. Prior research on human problem solving was based on two key assumptions: (i) that search through a problem space is a key element in solving problems, and (ii) that human thinking and problem solving are suboptimal. Recent results obtained independently in three laboratories have demonstrated the fundamental inadequacy of these two assumptions. It has been shown that humans produce optimal, or near-optimal solutions to difficult optimization tasks by performing minimal amounts of search. Existing decision research paradigms are not able to account for this sort of result; some new approaches are needed. For example, it appears that the mental representation of a problem is a key to peoples' effectiveness in solving difficult optimization problem, but mental representation is not much studied in current decision research. We will hold a three-day workshop where 15-20 scientists (psychologists and computer scientists working on optimization) from the United States, Canada, Australia, and Europe will discuss the current status of the field, future directions and ideas for collaborative work. The workshop will help establish a framework for research in this area over the coming decade and will also provide delegates the opportunity to discuss potential applications of recent findings about optimization by humans.

在过去的几年里，人们对研究人类如何解决困难的优化问题越来越感兴趣。 这些任务的共同特点是搜索空间巨大。 先前关于人类问题解决的研究基于两个关键假设：（i）搜索问题空间是解决问题的关键要素，以及（ii）人类思维和问题解决是次优的。 最近在三个实验室独立获得的结果表明，这两个假设的根本不足。 已经表明，人类通过执行最小量的搜索来产生困难的优化任务的最优或接近最优的解决方案。 现有的决策研究范式无法解释这种结果，需要一些新的方法。 例如，问题的心理表征似乎是人们解决困难优化问题的有效性的关键，但心理表征在当前的决策研究中并不多见。我们将举办一个为期三天的研讨会，来自美国、加拿大、澳大利亚和欧洲的15-20名科学家（从事优化工作的心理学家和计算机科学家）将讨论该领域的现状、未来方向和协作工作的想法。 该研讨会将有助于在未来十年内建立这一领域的研究框架，并为代表们提供机会，讨论有关人类优化的最新发现的潜在应用。