国家自然科学基金青年科学基金，61806102，面向通用博弈系统的策略表示与推理研究，2019/01-2021/12，主持

中央高校基本科研业务费专项资金资助项目，面向通用智能系统的知识表示与策略推理研究，2018/01-2019/12，主持

科技部监督司，推荐算法的伦理风险及其防范，2024/07-2024/12，参与

国家社科基金重大项目，17ZDA026，基于社交网络的信息流逻辑研究，2017/11-2022/12，参与

1. Zhang, H., Jiang, G.,Quan, D. A Theory of Formalisms for Representing Knowledge. AAAI, 2025.
2.  Ai D, Liu T, Jiang G, et al. StrategicReparameterization for Enhanced Inference in Imperfect Information Games: A  Neural Network Approach. International Conference on Intelligent Computing,ICIC, 2024.
3. Jiang, G., Perrussel, L.,Zhang, D.,Zhang, H., Zhang, Y., Game equivalence and expressive power of game descriptionlanguages: A bisimulation approach. Journal of Logic and Computation, 2023.
4. Wang, Y., Zhang, H., Jiang, G., A ConvolutionalNeural Network Approach to General Game Playing, ECAI, 2023.
5.  Yang, Y., Jiang, G., Zhang, Y.,Knowledge-Rich Influence Propagation Recommendation Algorithm Based on GraphAttention Networks. ADMA, 2023.   
6.  Zhang, H., Jiang, G., Characterizing theProgram Expressive Power of Existential Rule Languages. AAAI, 2022.
7. 梁思立,姜桂飞等. 基于蒙特卡洛树搜索的通用博弈系统的构建与优化研究[J]. 数据与计算发展前沿, 2022, 4(3): 66-77.
8.  Jiang, G., Zhang, D., Perrussel, L., andZhang, H., Epistemic GDL: A Logic for Representing and Reasoning aboutImperfect Information Games. Artificial Intelligence, 294: 103453, 2021.
9. Liang, S., Jiang, G., Zhang, Y.,Combining M-MCTS and Deep Reinforcement Learning for General Game Playing. DAI, 2021.
10. Zhang, H., Zhang, Y., Jiang, G.,Model-theoretic Characterizations of Existential Rule Languages. IJCAI, 2020.
11. Zhang, H.,  Zhang, Y., You, J., Feng, Z., Jiang, G.,Towards Universal Languages for Tractable Ontology Mediated Query Answering. AAAI,2020.
12. Jiang, G., Perrussel, L., Zhang, D.,Zhang, H., Zhang, Y., Game Equivalence and Bisimulation for Game DescriptionLanguage. PRICAI, 2019.
13. Jiang, G., Perrussel, L., Zhang, D.,Zhang, H., Zhang, Y., Characterizing the Expressivity of Game DescriptionLanguages. PRICAI, 2019.
14.  Jiang, G., Zhang, D., Perrussel, L., AHierarchical Approach to Judgment Aggregation with Abstentions. ComputationalIntelligence, 34: 104–123. 2018.
15. Jiang, G., Perrussel, L., Zhang, D., OnAxiomatization of Epistemic GDL. LORI, 2017.
16. Jiang, G., Zhang, D., Perrussel, L., andZhang, H., Epistemic GDL: A Logic for Representing and Reasoning aboutImperfect Information Games. IJCAI, 2016.
17. Jiang, G., Zhang, D., Perrussel, L., andZhang, H., A Logic for Collective Choice. AAMAS, 2015.
18. Lorini,E., Jiang, G., Perrussel, L., Trust-based Belief Change. ECAI, 2014.

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