TY - GEN
T1 - SNNAP
T2 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2013
AU - Collautti, Marco
AU - Malitsky, Yuri
AU - Mehta, Deepak
AU - O'Sullivan, Barry
PY - 2013
Y1 - 2013
N2 - The success of portfolio algorithms in competitions in the area of combinatorial problem solving, as well as in practice, has motivated interest in the development of new approaches to determine the best solver for the problem at hand. Yet, although there are a number of ways in which this decision can be made, it always relies on a rich set of features to identify and distinguish the structure of the problem instances. In this paper, we show how one of the more successful portfolio approaches, ISAC, can be augmented by taking into account the past performance of solvers as part of the feature vector. Testing on a variety of SAT datasets, we show how our new formulation continuously outperforms an unmodified/standard version of ISAC.
AB - The success of portfolio algorithms in competitions in the area of combinatorial problem solving, as well as in practice, has motivated interest in the development of new approaches to determine the best solver for the problem at hand. Yet, although there are a number of ways in which this decision can be made, it always relies on a rich set of features to identify and distinguish the structure of the problem instances. In this paper, we show how one of the more successful portfolio approaches, ISAC, can be augmented by taking into account the past performance of solvers as part of the feature vector. Testing on a variety of SAT datasets, we show how our new formulation continuously outperforms an unmodified/standard version of ISAC.
UR - https://www.scopus.com/pages/publications/84886577382
U2 - 10.1007/978-3-642-40994-3_28
DO - 10.1007/978-3-642-40994-3_28
M3 - Conference proceeding
AN - SCOPUS:84886577382
SN - 9783642409936
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 435
EP - 450
BT - Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Proceedings
Y2 - 23 September 2013 through 27 September 2013
ER -