Liu, B;
Feng, X;
Ren, J;
Mai, L;
Zhu, R;
Zhang, H;
Wang, J;
(2022)
A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning.
In: Koyejo, S and Mohamed, S and Agarwal, A and Belgrave, D and Cho, K and Oh, A, (eds.)
Advances in Neural Information Processing Systems 35 (NeurIPS 2022).
NeurIPS Proceedings: New Orleans, LA, USA.
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| Type: | Proceedings paper |
|---|---|
| Title: | A Theoretical Understanding of Gradient Bias in Meta-Reinforcement Learning |
| Event: | 2022 Conference on Neural Information Processing Systems (NeurIPS 2022) |
| ISBN-13: | 9781713871088 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://proceedings.neurips.cc/paper_files/paper/2... |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10174059 |
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