更多详细信息请见谷歌学术主页（https://scholar.google.com/citations?user=d7AoedYAAAAJ）
人工智能博弈研究组主页（https://gameai.njupt.edu.cn/）
[1] Guang Yang,
Zheng Xu, Jing Huo, Shangdong Yang, Tianyu Ding, Xingguo Chen, Yang Gao.
"State Abstraction via Deep Supervised Hash Learning." IEEE
TNNLS (2024).
[2] Xingguo Chen, Wangrong Qin, Yu Gong, Shangdong Yang, and Wenhao Wang. On
Convergence Rate of MRetrace. Mathematics 2024, 12, 2930.
[3] Wenhao Wang, Xingguo Chen, Yuwei Li, and
Cheng Zhu. Catch the Cyber Thief: A Multi-Dimensional Asymmetric Network
Attack–Defense Game. Applied Sciences, 2024, 14(20): 9234.
[4] 杨尚东,
余淼盈, 陈兴国, 陈蕾. 基于分组对比学习的序贯感知技能发现方法. 软件学报.2024.
[5] 董绍康，李超，杨光，葛振兴，曹宏业，陈武兵，杨尚东，陈兴国，李文斌，高阳. 混合博弈问题的求解与应用. 软件学报.2024.
[6] 陈兴国, 吕咏洲, 巩宇, 陈耀雄. 基于贝叶斯优化的强化学习广义不动点解逼近.
山东大学学报, 2024, 54(4): 21-34.
[7] Yongfeng Deng, Ruqin Shen, Xue Zhang, Yang Li, Xingguo
Chen, Rong-Rong He, Hao Tian, Shuqin Tang, Xiang Luo, Jing Li, Wan-Yang
Sun, Hongli Tan. Invisible hazards: Exploring neonicotinoid contamination and
its environmental risks in urban parks across China. Science of The Total
Environment, 2024, 954: 176715.
[8] Xingguo
Chen, Xingzhou Ma, Yang Li,
Guang Yang, Shangdong Yang and Yang Gao, Modified
Retrace for Off-Policy Temporal Difference Learning, Conference on
Uncertainty in Artificial Intelligence, 2023: 303-312 (CAAI A, CCF B).
[9] Xingguo
Chen, Yang Gao, and Ruili Wang,
Online selective kernel-based temporal
difference learning, IEEE TNNLS, 24(12): 1944-1956, 2013. （SCI一区,
CCF B）
[10] Xingguo
Chen, Guang Yang, Shangdong
Yang, et al. Online attentive kernel-based temporal difference learning.
Knowledge-Based Systems, 2023, 278: 110902 (CAAI B, CCF C).
[11] 陈兴国,孙丁源昊,杨光,杨尚东,高阳. 不动点视角下的强化学习算法综述. 计算机学报, 2023, 46(6):1246-1271.
[12] Xingguo Chen, Zening Chen, Dingyuanhao Sun, Yang Gao. Backtracking
Exploration for Reinforcement Learning. Proceedings of the Fifth
International Conference on Distributed Artificial Intelligence. 2023: 1-7.
[13] 张斐斐，葛季栋，李忠金，黄子峰，张胜，陈兴国，骆斌. 边缘计算中协作计算卸载与动态任务调度. 软件学报, 2023, 34(12): 5737-5756.
[14] Wenhao Wang, Dingyuanhao Sun, Feng Jiang, Xingguo
Chen, Cheng Zhu. Research and challenges of reinforcement learning in
cyber defense decision-making for intranet security. Algorithms, 2022,
15(4): 134.
[15] Guang Yang, Yang Li, Tian Huang, Qingyun Li, Xingguo
Chen. DHQN: a stable approach to remove target network from deep q-learning
network. 2021 IEEE 33rd International Conference on Tools with Artificial
Intelligence (ICTAI). IEEE, 2021: 1474-1479.
[16] Yong Liu, Weixun Wang, Yujing Hu, Jianye Hao, Xingguo
Chen, Yang Gao; Multi-Agent
Game Abstraction via Graph Attention Neural Network. AAAI 2020: 7211-7218. (CCF-A)
[17] Kangyang Chen; Hexia Chen; Chuanlong Zhou;
Yichao Huang; Xiangyang Qi; Ruqin Shen; Fengrui Liu; Min Zuo; Xinyi Zou;
Jinfeng Wang; Yan Zhang; Da Chen; Xingguo
Chen*; Yongfeng Deng*; Hongqiang Ren; Comparative analysis of surface water
quality prediction performance and identification of key water parameters using
different machine learning models based on big data, Water Research，2020(171).
（SCI一区，高被引）
[18] Chen,
Xingguo, Houtao Liu, Fengrui
Liu, Tian Huang, Ruqin Shen, Yongfeng Deng, Da Chen. "Two novelty learning models developed based on deep cascade forest to
address the environmental imbalanced issues: A case study of drinking water
quality prediction." Environmental Pollution 291 (2021): 118153. （SCI二区）
[19] Kangyang Chen, Xinyi Zou, Xingguo Chen,
Huihui Wang, An Automated Online Spam Detector Based on Deep Cascade Forest,
SciSec 2019.
[20] Feifei Zhang, Jidong Ge, Chifong Wong, Chuanyi
Li, Xingguo Chen, Sheng Zhang, Bin Luo, He Zhang, Victor Chang. Online
learning offloading framework for heterogeneous mobile edge computing system,
Journal of Parallel and Distributed Computing, 2019, 128: 167-183. (CCF-B)
[21] Fan Feng, Jikai Wu, Wei Sun, Yushuang Wu,
HuaKang Li, Xingguo Chen. Haze forecasting via deep LSTM. APWEB
2018. (CCF-C)
[22] Shangdong Yang, Yang Gao, Bo An, Hao Wang, and Xingguo
Chen, Efficient Average Reward Reinforcement Learning Using Constant
Shifting Values, AAAI 2016. (CCF-A)
[23] 陈兴国,俞扬. 强化学习及其在电脑围棋中的应用.自动化学报, 2016, 42(5):685-695.
[24] Wang, Hao, Yang Gao, and Xingguo Chen. RL-dot: A reinforcement
learning NPC team for playing domination games. IEEE Transactions on
Computational Intelligence and AI in Games (TCIAIG), 2010, 2(1): 17-26. (CCF-C)
[25] Xingguo Chen, Hao Wang, Weiwei Wang, Yinghuan Shi, and Yang Gao. Apply
ant colony optimization to Tetris. GECCO 2009. (CCF-C)
[26] 王皓，高阳，陈兴国. 强化学习中的迁移：方法和进展. 电子学报，强化学习中的迁移：方法和进展. 电子学报.36(12A): 39-43, 2008.
