Abstract
Meta-solver approaches exploit many individual solvers to potentially build a better solver. To assess the performance of meta-solvers, one can adopt the metrics typically used for individual solvers (e.g., runtime or solution quality) or employ more specific evaluation metrics (e.g., by measuring how close the meta-solver gets to its virtual best performance). In this paper, based on some recently published works, we provide an overview of different performance metrics for evaluating (meta-)solvers by exposing their strengths and weaknesses.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Journal of Artificial Intelligence Research |
| Vol/bind | 76 |
| Sider (fra-til) | 705-719 |
| ISSN | 1076-9757 |
| DOI | |
| Status | Udgivet - 17. mar. 2023 |
Bibliografisk note
Publisher Copyright:© 2023 AI Access Foundation. All rights reserved.
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