Affiliation:
1. Google Research, New York and Princeton University, New York, NY
2. University of Maryland, College Park, MD
3. MIT, Cambridge and EPEL, Switzerland
Abstract
Online auction is the 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 article, 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 (i.e., a knapsack constraint assigns a nonnegative cost to each secretary, and requires that the total cost of all the secretaries employed be no more than a budget value) 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
õ
(√
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
(√
n
)-competitive algorithm for the subadditive case. At the end, we consider some special cases of our general setting as well.
Funder
Division of Computing and Communication Foundations
University of Maryland Research and Scholarship Award
National Science Foundation
Office of Naval Research
Air Force Office of Scientific Research
Defense Advanced Research Projects Agency
Publisher
Association for Computing Machinery (ACM)
Subject
Mathematics (miscellaneous)
Cited by
46 articles.
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