Claessens, Mik (2024) A Comparative Analysis of Transfer Learning in Upside-Down Reinforcement Learning and Deep Q Networks. Bachelor's Thesis, Artificial Intelligence.
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Abstract
A study that compares the improvement that standard transfer learning can induce in the algorithm named Deep Q Networks and a relatively new algorithm called Upside-Down Reinforcement Learning.
| Item Type: | Thesis (Bachelor's Thesis) |
|---|---|
| Supervisor name: | Orzan, N. and Sabatelli, M. |
| Degree programme: | Artificial Intelligence |
| Thesis type: | Bachelor's Thesis |
| Language: | English |
| Date Deposited: | 07 Mar 2024 16:20 |
| Last Modified: | 07 Mar 2024 16:20 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/32030 |
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