A Novel Method for Improving the Training Efficiency of Deep Multi-Agent Reinforcement Learning
Deep reinforcement learning (RL) holds considerable promise to help address a variety of multi-agent problems in a dynamic and complex environment. In multi-agent scenarios, most tasks require multiple agents to cooperate and the number of agents has a negative impact on the training efficiency of r...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8845580/ |