Computational Feasibility of Structured Matching

Structured matching is a task-specific technique for selecting one choice out of a small number of alternatives based on a Manuscript received July 5 , 1988; revised March 31, 1989. Recommended for acceptance by R. De Mori. This work was supported by the National Science Foundation under Grant CBT-8703745, the Air Force Office of Scientific Research under Grant AFOSR-87-0090, and the National Heart, Lung, and Blood Institute under NIH Grant 1 R01 HL 38776-01. A. Goel was with the Laboratory for Artificial Intelligence Research, Department of Computer and Information Science, The Ohio State University, Columbus, OH 43210. He is now with the School of Information and Computer Science, Georgia Institute of Technology, Atlanta, GA 30322. T. By lander is with the Laboratory for Artificial Intelligence Research, Department of Computer and Information Science, The Ohio State University, Columbus, OH 43210. IEEE Log Number 8929958. given set of parameters. In structured matching, the knowledge and control for making a decision are integrated within a hierarchical structure. Each node in the hierarchy corresponds to a different aspect of the decision and contains knowledge for directly mapping the results of its children nodes (or selected parameters) into a choice on the subdecision. The root node selects the final choice for the decision. We formally characterize the task and strategy of structured matching and analyze its computational complexity. Structured matching, we helieve, captures the essence of what makes a range of decision-making problems computationally feasible to solve.