Imitation Learning using Reward-Guided DAgger
End-to-end autonomous driving can be approached by finding a policy function that maps observation (e.g. driving view of the road) to driving action. This is done by imitating an expert driver. This approach can be conducted by supervised learning, where the policy function is tuned to minimize the...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2020
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-287384 |