Utility estimation in large preference graphs using a search

Authors:
Henry Bediako-Asare;Scott Buffett;Michael W. Fleming
Affiliations:
University of New Brunswick, Fredericton, NB;National Research Council Canada, Fredericton, NB;University of New Brunswick, Fredericton, NB
Venue:
Canadian AI'11 Proceedings of the 24th Canadian conference on Advances in artificial intelligence
Year:
2011

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Abstract

Existing preference prediction techniques can require that an entire preference structure be constructed for a user. These structures, such as Conditional Outcome Preference Networks (COP-nets), can grow exponentially in the number of attributes describing the outcomes. In this paper, a new approach for constructing COP-nets, using A* search, is introduced. Using this approach, partial COP-nets can be constructed on demand instead of generating the entire structure. Experimental results show that the new method yields enormous savings in time and memory requirements, with only a modest reduction in prediction accuracy.