Artificial Intelligence - special issue on computational tradeoffs under bounded resources
Scalable Distributed Depth-First Search with Greedy Work Stealing
ICTAI '04 Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence
Experiments with massively parallel constraint solving
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
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Recent years have witnessed growing interest in parallelising constraint solving based on tree search (see [1] for a brief overview). One approach is search-space splitting in which different parts of the tree are explored in parallel (e.g. [2]). Another approach is the use of algorithm portfolios. This technique exploits the significant variety in performance observed between different algorithms and combines them in a portfolio [3]. In constraint solving, an algorithm can be a solver or a tuning of a solver. Portfolios have often been run in an interleaving fashion (e.g. [4]). Their use in a parallel context is more recent ([5], [1]).