Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4942074 | Artificial Intelligence | 2017 | 25 Pages |
Abstract
We show how to ground EML on a case study of thermal-aware workload dispatching. We use two learning methods, namely Artificial Neural Networks and Decision Trees and we show how to encapsulate the learned model in a number of optimization techniques, namely Local Search, Constraint Programming, Mixed Integer Non-Linear Programming and SAT Modulo Theories. We demonstrate the effectiveness of the EML approach by comparing our results with those obtained using expert-designed models.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Michele Lombardi, Michela Milano, Andrea Bartolini,