{"type":"ScholarlyArticle","title":"Deep Reinforcement Learning with Hierarchical Structures","authors":[{"name":"Siyuan Li","slug":"siyuan-li","given":"Siyuan","family":"Li","affiliation":""}],"abstract":"Hierarchical reinforcement learning (HRL), which enables control at multiple time scales, is a promising paradigm to solve challenging and long-horizon tasks. In this paper, we briefly introduce our work in bottom-up and top-down HRL and outline the directions for future work.","doi":"10.24963/ijcai.2021/681","url":"https://ijcai.org/proceedings/2021/681","pdf":"https://ijcai.org/proceedings/2021/0681.pdf","markdown":"https://ijcai.org/proceedings/2021/681.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/681","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":681,"pages":{"first":4899,"last":4900},"keywords":["Machine Learning: Reinforcement Learning"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}