GLIB: Efficient Exploration for Relational Model-Based Reinforcement Learning via Goal-Literal Babbling
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Show full item recordDate issued
2021Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence LaboratoryJournal
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