GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling
Name
17400-Article Text-20894-1-2-20210518.pdf
Description
Published version
Size
2.73 MB
Format
Adobe PDF
Checksum (MD5)
6f9e62ee3a3b90e1d31fd549b6eb07b9
Author(s)
Chitnis, Rohan
Silver, Tom
Tenenbaum, Joshua
Kaelbling, Leslie Pack
Lozano-Perez, Tomas
Intelligence, Assoc Advancement Artificial
Date Issued
2021
Journal
THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE
Citation
Chitnis, Rohan, Silver, Tom, Tenenbaum, Joshua, Kaelbling, Leslie Pack, Lozano-Perez, Tomas et al. 2021. "GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling." THIRTY-FIFTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, THIRTY-THIRD CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE AND THE ELEVENTH SYMPOSIUM ON EDUCATIONAL ADVANCES IN ARTIFICIAL INTELLIGENCE, 35.
Version
Final published version
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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