Complexity of finding embeddings in a k-tree
SIAM Journal on Algebraic and Discrete Methods
Instance-Based Learning Algorithms
Machine Learning
Logic programs with stable model semantics as a constraint programming paradigm
Annals of Mathematics and Artificial Intelligence
A complete anytime algorithm for treewidth
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
The DLV system for knowledge representation and reasoning
ACM Transactions on Computational Logic (TOCL)
Cross-disciplinary perspectives on meta-learning for algorithm selection
ACM Computing Surveys (CSUR)
Heuristic Methods for Hypertree Decomposition
MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Bounded treewidth as a key to tractability of knowledge representation and reasoning
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Algorithms for propositional model counting
Journal of Discrete Algorithms
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Answer-set programming with bounded treewidth
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Treewidth computations I. Upper bounds
Information and Computation
A practical algorithm for finding optimal triangulations
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
A dynamic-programming based ASP-solver
JELIA'10 Proceedings of the 12th European conference on Logics in artificial intelligence
Learning and using domain-specific heuristics in ASP solvers
AI Communications - Answer Set Programming
A portfolio solver for answer set programming: preliminary report
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
A New Tree-Decomposition Based Algorithm for Answer Set Programming
ICTAI '11 Proceedings of the 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence
A branch and bound algorithm for exact, upper, and lower bounds on treewidth
AAIM'06 Proceedings of the Second international conference on Algorithmic Aspects in Information and Management
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A promising approach to tackle intractable problems is given by a combination of decomposition methods with dynamic algorithms. One such decomposition concept is tree decomposition. However, several heuristics for obtaining a tree decomposition exist and, moreover, also the subsequent dynamic algorithm can be laid out differently. In this paper, we provide an experimental evaluation of this combined approach when applied to reasoning problems in propositional answer set programming. More specifically, we analyze the performance of three different heuristics and two different dynamic algorithms, an existing standard version and a recently proposed algorithm based on a more involved data structure, but which provides better theoretical runtime. The results suggest that a suitable combination of the tree decomposition heuristics and the dynamic algorithm has to be chosen carefully. In particular, we observed that the performance of the dynamic algorithm highly depends on certain features (besides treewidth) of the provided tree decomposition. Based on this observation we apply supervised machine learning techniques to automatically select the dynamic algorithm depending on the features of the input tree decomposition.