吉建民

E- Mail：jianmin@ustc.edu.cn

個人主頁：http://staff.ustc.edu.cn/~jianmin/ 

實驗室主頁：http://ai.ustc.edu.cn 

  

主要研究方向：認知機器人，深度強化學習，知識表示與推理。

  

吉建民，中國科學技術大學副教授，碩士生導師。在中國科學技術大學計算機學院獲得學士、博士學位，曾任香港科技大學博士後，阿爾伯塔大學、卡內基梅隆大學訪問學者。主要研究方向為認知機器人、知識表示與推理、深度強化學習。連續10年負責中科大“可佳”“佳佳”機器人認知模塊，並獲世界冠軍。在人工智能、機器人頂級期刊和會議發表論文多篇。長期擔任JAIR、AAAI、IJCAI、AAMAS、KR、ICRA等國際頂級期刊和會議（高級）程序委員會委員。

主要工程項目：

  

獲獎情況：

  • 認知技術被《Artificial Intelligence》評為機器人認知方麵十年最佳技術成果（Best Technique Solution）；

  • 獲得第23屆國際人工智能聯合大會（IJCAI-13）最佳自主機器人獎（Best Autonomous Robotics Video）

    

十篇代表性論著：

  1. Jianmin Ji, Fangfang Liu, and Jia-Huai You*. Well-founded operators for normal hybrid MKNF knowledge bases. Theory and Practice of Logic Programming 17.5-6, pages 889-905, 2017.

  2. Jianmin Ji, Hai Wan*, Kewen Wang, Zhe Wang, Chuhan Zhang, and Jiangtao Xu. Eliminating Disjunctions in Answer Set Programming by Restricted Unfolding. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), pages 1130-137, 2016.

  3. Jianmin Ji, Yisong Wang*, and Jiahuai You. On Forgetting Postulates in Answer Set Programming. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI-15), pages 3076-3083, 2015.

  4. Jianmin Ji, Hai Wan*, Ziwei Huo, and Zhenfeng Yuan. Simplifying a Logic Program Using Its Consequences. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI-15), pages 3069-3075, 2015.

  5. Jianmin Ji, Hai Wan*, and Peng Xiao. On Elementary Loops and Proper Loops for Disjunctive Logic Programs. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), pages 1518-1524, 2015.

  6. Jianmin Ji, Hai Wan*, Ziwei Huo, and Zhenfeng Yuan. Splitting a Logic Program Revisited. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI-15), pages 1511-1517, 2015.

  7. Jianmin Ji and Fangzhen Lin*. Position Systems in Dynamic Domains. Journal of Philosophical Logic (JPL) 44(2), pages 147-161, 2015.

  8. Jianmin Ji and Xiaoping Chen*. A Weighted Causal Theory for Acquiring and Utilizing Open Knowledge. International Journal of Approximate Reasoning (IJAR) 55(9), pages 2071-2082, 2014.

  9. Jianmin Ji, Hai Wan*, Peng Xiao, Ziwei Huo, and Zhanhao Xiao. Elementary Loops Revisited. In Proceedings of the 28th AAAI Conference on Artificial Intelligence (AAAI-14), pages 1063-1069, 2014.

  10. Xiaoping Chen, Jianmin Ji*, and Fangzhen Lin. Computing loops with at most one external support rule. ACM Transactions on Computational Logic (TOCL) 14(1), pages 3-37, 2013.


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