Submodular Secretary Problem and Extensions
Name
MIT-CSAIL-TR-2010-002.pdf
Size
310.99 KB
Format
Adobe PDF
Checksum (MD5)
56d535ae3161cac7b922239116343207
Author(s) • •
Zadimoghaddam, Morteza
Hajiaghayi, MohammadTaghi
Bateni, MohammadHossein
Advisor(s)
Erik Demaine
Date Issued
February 1, 2010
Series/Report no.
MIT-CSAIL-TR-2010-002
Abstract
Online auction is an essence of many modern markets, particularly networked markets, in which information about goods, agents, and outcomes is revealed over a period of time, and the agents must make irrevocable decisions without knowing future information. Optimal stopping theory, especially the classic "secretary problem", is a powerful tool for analyzing such online scenarios which generally require optimizing an objective function over the input. The secretary problem and its generalization the "multiple-choice secretary problem" were under a thorough study in the literature. In this paper, we consider a very general setting of the latter problem called the "submodular secretary problem", in which the goal is to select k secretaries so as to maximize the expectation of a (not necessarily monotone) submodular function which defines efficiency of the selected secretarial group based on their overlapping skills. We present the first constant-competitive algorithm for this case. In a more general setting in which selected secretaries should form an independent (feasible) set in each of l given matroids as well, we obtain an O(l log^2 r)-competitive algorithm generalizing several previous results, where r is the maximum rank of the matroids. Another generalization is to consider l knapsack constraints instead of the matroid constraints, for which we present an O(l)-competitive algorithm. In a sharp contrast, we show for a more general setting of "subadditive secretary problem, there is no o~(sqrt(n))-competitive algorithm and thus submodular functions are the most general functions to consider for constant competitiveness in our setting. We complement this result by giving a matching O(sqrt(n))-competitive algorithm for the subadditive case. At the end, we consider some special cases of our general setting as well.
Terms of Use
Creative Commons Attribution 3.0 Unported
Persistent DSpace Link