Tractable Pareto optimization of temporal preferences

Authors:
Lina Khatib;Paul Morris;Robert Morris;Kristen Brent Venable
Affiliations:
Kestrel Technology and Computational Sciences Division, NASA Ames Research Center, Moffett Field, CA;Computational Sciences Division, NASA Ames Research Center, Moffett Field, CA;-;Department of Pure and Applied Mathematics, University of Padova, Padova, Italy
Venue:
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Year:
2003

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Abstract

This paper focuses on temporal constraint problems where the objective is to optimize a set of local preferences for when events occur. In previous work, a subclass of these problems has been formalized as a generalization of Temporal CSPs, and a tractable strategy for optimization has been proposed, where global optimality is defined as maximizing the minimum of the component preference values. This criterion for optimality, which we call "Weakest Link Optimization" (WLO), is known to have limited practical usefulness because solutions are compared only on the basis of their worst value; thus, there is no requirement to improve the other values. To address this limitation, we introduce a new algorithm that rc-applies WLO iteratively in a way that leads to improvement of all the values. We show the value of this strategy by proving that, with suitable preference functions, the resulting solutions are Pareto Optimal.