Comparing Apples and Oranges Through Partial Orders: An Empirical Approach
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Kingston, Peter
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Abstract
In this paper, we try to understand what people
mean when they say that two objects are "similar." This is an
important question in the area of human-robot interactions,
where robots must interpret human movements in order to act
in a "similar" manner. Specifically, we assume that we are given
a collection of empirically generated pairwise comparisons
between a subset of so-called alternatives (members of a given
set), which produces a partial order over the set of alternatives.
Based on this partial order, an inverse optimization problem
is solved, producing a cost associated with each alternative
that is consistent with the partial order. This cost is, moreover,
assumed to be generative in that it can be used to select the
globally best alternative. An experimental study involving the
comparison of apples and oranges is presented to highlight the
operation of the proposed approach.
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Date
2009-06
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Text
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Proceedings