Optimizing the Junction-Tree-Based Reinforcement Learning Algorithm for Network-Wide Signal Coordination
This study develops three measures to optimize the junction-tree-based reinforcement learning (RL) algorithm, which will be used for network-wide signal coordination. The first measure is to optimize the frequency of running the junction-tree algorithm (JTA) and the intersection status division. The...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/6489027 |
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