Stabilising experience replay for deep multi-agent reinforcement learning
Many real-world problems, such as network packet routing and urban traffic control, are naturally modeled as multi-agent reinforcement learning (RL) problems. However, existing multi-agent RL methods typically scale poorly in the problem size. Therefore, a key challenge is to translate the success o...
| Автори: | , , , , , |
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| Формат: | Conference item |
| Опубліковано: |
PMLR
2017
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