Hierarchical multi-agent reinforcement learning for cooperative tasks with sparse rewards in continuous domain
Author:
Funder
National Natural Science Foundation of China
Natural Science Foundation of Jiangsu Province
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-08882-6.pdf
Reference47 articles.
1. Wang Y, Dong L, Sun C (2020) Cooperative control for multi-player pursuit-evasion games with reinforcement learning. Neurocomputing 412:101–114
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3. Zhang Z, Wang D, Gao J (2021) Learning automata-based multiagent reinforcement learning for optimization of cooperative tasks. IEEE Trans Neural Netw Learn Syst 32(10):4639–4652
4. Shike Y, Jingchen L, Haobin S (2023) Mix-attention approximation for homogeneous large-scale multi-agent reinforcement learning. Neural Comput Appl 35(4):3143–3154
5. Tan M (1993) Multi-agent reinforcement learning-independent vs. cooperative agent. In: Proceedings of the 10th International Conference on Machine Learning, pp 330–337
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