A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning
Name
kim21g.pdf
Description
Published version
Size
1.16 MB
Format
Adobe PDF
Checksum (MD5)
cf5df186e509713dbe55a89f4f2425da
Author(s)
Kim, Dong-Ki
Liu, Miao
Riemer, Matthew
Sun, Chuangchuang
Abdulhai, Marwa
Habibi, Golnaz
Lopez-Cot, Sebastian
Tesauro, Gerald
How, Jonathan P
Date Issued
2021
Journal
INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139
Citation
Kim, Dong-Ki, Liu, Miao, Riemer, Matthew, Sun, Chuangchuang, Abdulhai, Marwa et al. 2021. "A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning." INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139, 139.
Version
Final published version
MIT Department
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
MIT-IBM Watson AI Lab
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://proceedings.mlr.press/v139/kim21g.html
