Accelerated sim-to-real deep reinforcement learning: learning collision avoidance from human player

Niu, Hanlin, Ji, Ze ORCID: https://orcid.org/0000-0002-8968-9902, Arvin, Farshad, Lennox, Barry, Yin, Hujun and Carrasco, Joaquin 2021. Accelerated sim-to-real deep reinforcement learning: learning collision avoidance from human player. Presented at: 2021 IEEE/SICE International Symposium on System Integration (SII2021), Iwaki, Fukushima, Japan, 11-14 January 2021. Item availability restricted.

PDF - Accepted Post-Print Version Restricted to Repository staff only Download (4MB)

Item Type:	Conference or Workshop Item (Paper)
Status:	In Press
Schools:	Engineering
Additional Information:	"© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."
Date of First Compliant Deposit:	8 February 2021
Date of Acceptance:	5 October 2020
Last Modified:	09 Nov 2022 10:07
URI:	https://orca.cardiff.ac.uk/id/eprint/138349

Citation Data

Cited 11 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item