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A key focus of the paper is a discussion of the algorithm engineering principles necessary to mitigate the NP-complete nature of practical problems.
Section 4 summarizes the theoretical foundations of the proposed algorithms and introduces the concepts of, e.g., fixed-parameter tractability and expression trees, which are needed for the subsequent discussion of the algorithm design.
Further discussion of the algorithm's accuracy is included.
A LCP minimises the sum of costs of all cells along the path (for detailed description and discussion of the algorithm, see [ 76]).
Understandably, the authors did not want to repeat the discussion of the algorithm given previously by Balakrishnan et al. and also briefly in their PNAS paper (Kamisetty et al., 2013).
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A discussion of the algorithms is beyond the scope of this paper.
For a more technical discussion of the algorithms used in defining these measures and for a more detailed description on model building, see the Overview, Design Concepts, and Details (ODD) available as an Additional file 1, which follows the protocol for describing agent-based models as suggested by Grimm et al. [ 43, 49].
We thank Polly Fordyce, Victoria Newman, J. Graham Ruby and Peter Skewes-Cox for critical reading of the manuscript and Michael Cary for insightful discussions on the algorithm.
Analogously to our discussion of the R&E algorithm, one obtains space and time complexities of the sparsified algorithm in terms of the length of candidate lists and the total number of candidates.
The proposed algorithm is detailed in Section 2. Section 3 presents the experimental results and a discussion of the proposed algorithm.
The formulation and discussion of the proposed algorithm are given in Section 2. In Section 3, respectively.
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