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Optimising the Optimiser: Meta NeuroEvolution for Artificial Intelligence Problems
Since reinforcement learning algorithms have to fully solve a task in order to evaluate a set of hyperparameter values, conventional hyperparameter tuning methods can be highly sample inefficient and computationally expensive. Many widely used reinforcement learning architectures originate from scie...
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| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2022
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