A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
and development in all areas of automation
Volume 11
Issue 11
IEEE/CAA Journal of Automatica Sinica
| Citation: | B. Yang, C. Tang, Y. Liu, G. Wen, and G. Chen, “A linear programming-based reinforcement learning mechanism for incomplete-information games,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 11, pp. 2340–2342, Nov. 2024. doi: 10.1109/JAS.2024.124464
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L. Xue, C. Sun, D. Wunsch, Y. Zhou, and F. Yu, “An adaptive strategy via reinforcement learning for the prisoners dilemma game,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 1, pp. 301–310, Jan. 2018. doi: 10.1109/JAS.2017.7510466
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W. Zha, J. Chen, and Z. Peng, “Dynamic multi-team antagonistic games model with incomplete information and its application to multi-UAV,” IEEE/CAA J. Autom. Sinica, vol. 2, no. 1, pp. 74–84, Jan. 2015. doi: 10.1109/JAS.2015.7032908
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H. Wang, T. Huang, X. Liao, H. Abu-Rub, and G. Chen, “Reinforcement learning for constrained energy trading games with incomplete information,” IEEE Trans. Cybern., vol. 47, no. 10, pp. 3404–3416, Oct. 2017. doi: 10.1109/TCYB.2016.2539300
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D. Shen, “Iterative learning control with incomplete information: A survey,” IEEE/CAA J. Autom. Sinica, vol. 5, no. 5, pp. 885–901, Sep. 2018. doi: 10.1109/JAS.2018.7511123
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G. Wen, J. Fu, P. Dai, and J. Zhou, “DTDE: A new cooperative multiagent reinforcement learning framework,” The Innovation, vol. 2, no. 4, p. 100162, Sep. 2021. doi: 10.1016/j.xinn.2021.100162
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