Monteiro, JuarezGavenski, NathanMeneguzzi, FelipeBarros, Rodrigo C.2023-08-232023-08-232023-04-21Monteiro, J, Gavenski, N, Meneguzzi, F & Barros, R C 2023 'Self-Supervised Adversarial Imitation Learning' ArXiv. https://doi.org/10.48550/arXiv.2304.10914ArXiv: http://arxiv.org/abs/2304.10914v1ORCID: /0000-0003-3549-6168/work/141302256https://hdl.handle.net/2164/21527This paper has been accepted in the International Joint Conference on Neural Networks (IJCNN) 2023 This work was supported by UK Research and Innovation [grant number EP/S023356/1], in the UKRI Centre for Doctoral Training in Safe and Trusted Artificial Intelligence (www.safeandtrustedai.org) and made possible via King’s Computational Research, Engineering and Technology Environment (CREATE) [27].8405989engcs.LGcs.AIUK Research and Innovation (UKRI)EP/S023356/1Preprint10.48550/arXiv.2304.10914