In solving decisionmaking problems, both human and artificial decisionmakers use scales of measurement based on subject judgements to choose among alternative courses of action or to select optimal strategies. With this in mind, the investigator is attempting to understand in a systematic way the limitations that properties of scales of measurement place on the conclusions one may meaningfully draw using such scales. He is studying such limitations for conclusions from the solutions to problems of optimization, from averaging or merging techniques to combine individual judgements, from relative scores used to choose among alternative technologies or alternative heuristics, and from models used for solving practical problems involving resources allocation, communications, transportation, technology assessment, etc. An important aspect of the work concerns the implications of these limitations for the use of scales of measurement in problem solving by human or artificial problem solvers. The investigator will attempt to develop the theory of meaningful statements and to study various theoretical questions about the theory of scales of measurement which underly its use in the analysis of practical decisionmaking problems.
