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

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巨大的搜索空间。先前关于人类解决问题的研究基于两个关键假设：(i)在问题空间中搜索是解决问题的关键因素；（ii）人类的思维和解决问题的能力是次优的。最近在三个实验室独立获得的结果表明，这两种假设根本不充分。研究表明，人类通过进行最少的搜索，可以对困难的优化任务产生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有效解决困难优化问题的关键，但在当前的决策研究中，心理表征的研究并不多。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、未来的方向和协作工作的想法。研讨会将有助于在未来十年建立这一领域的研究框架，并将为代表们提供机会，讨论关于人类优化的最新发现的潜在应用。

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.