Increasingly Complex Environments in Deep Reinforcement Learning
In this thesis, we used deep reinforcement learning to train autonomous agents and evaluated the impact of increasing the complexity of the training environment over time. This was compared to using a fixed complexity. Also, we investigated the impact of using a pre-trained agent as a starting point...
| Main Authors: | , |
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2019
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| Subjects: | |
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259193 |