CORTAMBERT, M. Pierre (2021) Reproductibilité de l'apprentissage par renforcement PRE - Research Project, ENSTA.
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Abstract
Species conservation management is a major environmental concern. Reinforcement learning algorithms allow today advances in several fields. These algorithms can help to solve environmental problems. However, one of computer science’s biggest challenge in research concerns the reproducibility of reinforcement learning. We are thus interested doing reinforcement learning with a randomized initial conditional and will evaluate the relevance of this method in a reproducibility concern.
Item Type: | Thesis (PRE - Research Project) |
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Subjects: | Mathematics and Applications Earth Sciences and Environmental Engineering |
ID Code: | 8461 |
Deposited By: | pierre Cortambert |
Deposited On: | 16 mars 2022 16:48 |
Dernière modification: | 16 mars 2022 16:48 |
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