Tensor-Based Efficient Federated Reinforcement Learning for Cyber-Physical-Social Intelligence
Reinforcement Learning (RL) serves as a fundamental learning paradigm in the field of artificial intelligence, enabling decision-making policies through interactions with environments. However, traditional RL methods encounter challenges when dealing with large-scale or continuous state spaces due t...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2025-06-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2025.9020036 |
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