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.
