Abstract
We study stochastic submodular maximization problem with respect to a cardinality constraint. Our model can capture the effect of uncertainty in different problems, such as cascade effects in social networks, capital budgeting, sensor placement, etc. We study non-adaptive and adaptive policies and give optimal constant approximation algorithms for both cases. We also bound the adaptivity gap of the problem between 1.21 and 1.59. © 2008 Springer Berlin Heidelberg.
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CITATION STYLE
Asadpour, A., Nazerzadeh, H., & Saberi, A. (2008). Stochastic submodular maximization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5385 LNCS, pp. 477–489). https://doi.org/10.1007/978-3-540-92185-1_53
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