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Abstract:
We compare the economic efficiency achieved by multiattribute auctions that use an accurate GAI modeling of preferences, with a multiattribute auction that is limited to an additive representation. We draw random GAI-structured utility functions with various internal structures, generate additive functions that approximate the GAI utility, and compare the performance of the auctions using the two representations. We draw general preference modeling and methodological conclusions from both the process and the results.