New Techniques for Algorithm Portfolio Design
Abstract
We present and evaluate new techniques for designing algorithm portfolios. In our view, the problem has both a scheduling aspect and a machine learning aspect. Prior work has largely addressed one of the two aspects in isolation. Building on recent work on the scheduling aspect of the problem, we present a technique that addresses both aspects simultaneously and has attractive theoretical guarantees. Experimentally, we show that this technique can be used to improve the performance of state-of-the-art algorithms for Boolean satisfiability, zero-one integer programming, and A.I. planning.
Cite
Text
Streeter and Smith. "New Techniques for Algorithm Portfolio Design." Conference on Uncertainty in Artificial Intelligence, 2008.Markdown
[Streeter and Smith. "New Techniques for Algorithm Portfolio Design." Conference on Uncertainty in Artificial Intelligence, 2008.](https://mlanthology.org/uai/2008/streeter2008uai-new/)BibTeX
@inproceedings{streeter2008uai-new,
title = {{New Techniques for Algorithm Portfolio Design}},
author = {Streeter, Matthew J. and Smith, Stephen F.},
booktitle = {Conference on Uncertainty in Artificial Intelligence},
year = {2008},
pages = {519-527},
url = {https://mlanthology.org/uai/2008/streeter2008uai-new/}
}