Tesseract: tensorised actors for multi−agent reinforcement learning
Reinforcement Learning in large action spaces is a challenging problem. This is especially true for cooperative multi-agent reinforcement learning (MARL), which often requires tractable learning while respecting various constraints like communication budget and information about other agents. In thi...
| Main Authors: | , , , , , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
PMLR
2021
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