Results
eNauka >
Results >
Multi-Agent Actor-Critic Multitask Reinforcement Learning based on GTD(1) with Consensus
| Title: | Multi-Agent Actor-Critic Multitask Reinforcement Learning based on GTD(1) with Consensus | Authors: | Stankovic, Milos S. |
Issue Date: | 2022 | Publication: | 2022 IEEE 61st Conference on Decision and Control (CDC) | ISSN: | 2576-2370![]() Search Idenfier |
Publisher: | IEEE | Type: | Conference Paper | ISBN: | 978-1-6654-6761-2 Search Idenfier |
DOI: | 10.1109/cdc51059.2022.9992951 | WoS-ID: | 000948128103137 | Scopus-ID: | 2-s2.0-85147029098 | URI: | https://ieeexplore.ieee.org/abstract/document/9992951 https://enauka.gov.rs/handle/123456789/791356 http://ezaposleni.singidunum.ac.rs/rest/sciNaucniRezultati/oai/record/1/10233 |
URL: | https://ieeexplore.ieee.org/abstract/document/9992951 | Metadata source: | (Preuzeto iz ORCID-a) Stanković, Miloš | M-category: | Mp. category will be shown later |
Items in eNauka are protected by copyright, with all rights reserved, unless otherwise indicated.
