IJCAI 2024poster0 citations
Anytime Sorting Algorithms
Emma Caizergues, François Durand, Fabien Mathieu
Abstract
This paper addresses the anytime sorting problem, aiming to develop algorithms providing tentative estimates of the sorted list at each execution step. Comparisons are treated as steps, and the Spearman's footrule metric evaluates estimation accuracy. We propose a general approach for making any sorting algorithm anytime and introduce two new algorithms: multizip sort and Corsort. Simulations showcase the superior performance of both algorithms compared to existing methods. Multizip sort keeps a low global complexity, while Corsort produces intermediate estimates surpassing previous algorithms.
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BibTeX
@inproceedings{ijcai2024p785,
title = {Anytime Sorting Algorithms},
author = {Caizergues, Emma and Durand, François and Mathieu, Fabien},
booktitle = {Proceedings of the Thirty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-24}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Kate Larson},
pages = {7101--7108},
year = {2024},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2024/785},
url = {https://doi.org/10.24963/ijcai.2024/785},
}