{"type":"ScholarlyArticle","title":"Robot Manipulation Learning Using Generative Adversarial Imitation Learning","authors":[{"name":"Mohamed Khalil Jabri","slug":"mohamed-khalil-jabri","given":"Mohamed Khalil","family":"Jabri","affiliation":"IMT Atlantique , Lab-STICC , UMR 6285 , team RAMBO , F-29238 Brest , France; The University of Adelaide , SA , Australia; CROSSING IRL CNRS 2010"}],"abstract":"Imitation learning allows learning complex behaviors given demonstrations. Early approaches belonging to either Behavior Cloning or Inverse Reinforcement Learning were however of limited scalability to complex environments. A more promising approach termed as Generative Adversarial Imitation Learning tackles the imitation learning problem by drawing a connection with Generative Adversarial Networks. In this work, we advocate the use of this class of methods and investigate possible extensions by endowing them with global temporal consistency, in particular through a contrastive learning based approach.","doi":"10.24963/ijcai.2021/678","url":"https://ijcai.org/proceedings/2021/678","pdf":"https://ijcai.org/proceedings/2021/0678.pdf","markdown":"https://ijcai.org/proceedings/2021/678.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/678","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Doctoral Consortium","track":"Doctoral Consortium","number":678,"pages":{"first":4893,"last":4894},"keywords":["Machine Learning: Unsupervised Learning","Robotics: Learning in Robotics","Machine Learning: Adversarial Machine Learning","Machine Learning: Reinforcement Learning"],"videos":[],"references":[{"position":1,"raw":"[Andrychowicz et al., 2017] Marcin Andrychowicz, Filip Wolski, Alex Ray, Jonas Schneider, Rachel Fong, Peter Welinder, Bob McGrew, Josh Tobin, OpenAI Pieter Abbeel, and Wojciech Zaremba. 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