Non-Additive Utility Theories for Uncertain Alterations Into Mixed Consequences

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Luce Experimental studies and attempts by decision analysists to use extant models to predict people's behavior for decisions involving mixed consequences of both gains and losses have not been very successful. Examples where trouble has been seen is in medical decision making. Because of the great importance of such applications, it is urgent that better models be developed and tested. Recent theoretical work by the PI has shown why the troubles may arise. He has shown under very plausible, empirically testable conditions that the computations one should use considerably more complex expressions than the weighted averages of utilities of consequences that are commonly employed. Indeed, he derived two distinct mathematical forms from slightly different assumptions. One goal of the project is to pit these assumptions against one another directly and to see empirically which is more accurate. Also, attempts will be made to determine whether these new expressions actually provide improved predictions of observed behavior. Some numerical fitting will be based on existing data, but considerable additional data are needed for more thorough-going tests. The PI will continue to develop the area theoretically. In particular, he will focus considerable attention on the form of the weighting functions whose properties as far less specified than are those of the utility function.