所属研究所、院系:
量子计算与计算机理论研究所

职称:
教授

E-mail:
ymliu@mail.sysu.edu.cn

办公地点:
计算机学院楼




教师简介:
刘咏梅，中山大学计算机学院教授，博士生导师。于加拿大多伦多大学计算机科学系获博士学位。主要研究方向为人工智能中的知识表示与推理。研究成果持续发表于国际人工智能会议IJCAI和AAAI上。
欢迎对人工智能知识表示与推理感兴趣的同学加入本研究组！

研究领域:
人工智能，知识表示与推理，认知机器人学，智能体程序的自动生成和验证
目前正在开展的研究工作：
1.通用规划（generalized planning）及其应用：自动规划是人工智能的核心组成部分。经典规划研究给定世界的一个初始状态和一个目标，如何自动生成一个动作序列以达到目标。通用规划旨在为相同论域的多个经典规划实例生成一个带分支和循环的通解。通用规划和程序自动生成密切相关。
2.符号推理（symbolic reasoning）和机器学习的有效结合及其在自然语言处理中的应用：人类的智能主要包括归纳总结和逻辑演绎，分别对应于基于机器学习和基于符号推理的人工智能。如何有效地将逻辑推理和机器学习相结合是未来人工智能的一个重要研究方向。
3.多智能体认知规划（multi-agent epistemic planning）及高阶信念变化（higher-order belief change）: 许多智能任务涉及多个智能体的交互，需要对智能体的知识和信念及其变化进行推理。多智能体认知规划研究如何通过执行具有认知前提和效果的动作实现认知目标。
4.关于策略能力的推理（reasoning about strategic abilities）：多智能体系统的很多性质是基于策略能力的，即一组智能体是否有一个集体策略实现一个目标，无论其他智能体如何行动。我们关注如何对智能体的策略能力进行表示和推理，如何进行策略的自动验证和生成。

教育背景:
多伦多大学计算机科学硕士，博士，武汉大学计算机科学学士

工作经历:
2007年12月至今，中山大学，教授，博士生导师

海外经历:
访问教授: 荷兰阿姆斯特丹大学，意大利罗马大学，法国图卢兹大学，德国亚琛工业大学，澳洲新南威尔士大学

科研项目:
1. 国家自然科学基金项目， 通用规划的理论基础及有效求解方法研究
2. 国家自然科学基金项目， 多智能体动作推理及高级控制的理论与技术研究
3. 国家自然科学基金项目， 情景演算中的关键推理技术及其应用研究

教授课程:
研究生课程：数理逻辑，知识表示与推理
本科生课程：离散数学，人工智能，数理逻辑

代表性论著:
1. Z. Liu,?L. Xiong, Y. Liu, Y. Lespérance, R. Xu and H. Shi. A Modal Logic for Joint Abilities under Strategy Commitments. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (IJCAI-20), 2020.?
2. K.?Luo,?Y. Liu, Y. Lespérance, and Z. Lin. Agent Abstraction via Forgetting in the Situation Calculus. In Proceedings of the Twenty-Fourth European Conference on Artificial Intelligence (ECAI-20), 2020.
3. J. Li and Y. Liu. Automatic Verification of Liveness Properties in the Situation Calculus. In Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), 2020.
4. K. Luo and Y. Liu. Automatic Verification of FSA Strategies via Counterexample-Guided Local Search for Invariants. In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19), 2019.
5. L. Fang,?Y. Liu and?H. van Ditmarsch. Forgetting in multi-agent modal logics.?Artificial Intelligence, 266:?51-80, 2019.
6. Q. Liu and Y. Liu. Multi-agent Epistemic Planning with Common Knowledge. In?Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18), 2018.
7 X. Huang, B. Fang, H. Wan and Y. Liu. A General Multi-agent Epistemic Planner Based on Higher-order Belief Change.?In?Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17), 2017.
8 P. Mo, N. Li and Y. Liu. Automatic Verification of Golog Programs via Predicate Abstraction. In?Proceedings of the Twenty-Second European Conference on Artificial Intelligence (ECAI-16), 2016.
9 L. Xiong and Y. Liu. Strategy Representation and Reasoning in the Situation Calculus. In?Proceedings of the Twenty-Second European Conference on Artificial Intelligence (ECAI-16), 2016. [pdf]
10. Xiong and Y. Liu. Strategy Representation and Reasoning for Incomplete Information Concurrent Games in the Situation Calculus. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16), 2016.
11. L. Fang, Y. Liu and H. van Ditmarsch. Forgetting in Multi-Agent Modal Logics. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16), 2016.
12. H. Wan, R. Yang, L. Fang, Y. Liu and H. Xu. A Complete Epistemic Planner without the Epistemic Closed World Assumption. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI-15), 2015.
13. L. Fang, Y. Liu and X. Wen. On the Progression of Knowledge and Belief for Nondeterministic Actions in the Situation Calculus. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI-15), 2015.
14. N. Li and Y. Liu. Automatic Verification of Partial Correctness of Golog Programs. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI-15), 2015.
15. X. Wang and Y. Liu. Automated fault localization via hierarchical multiple predicate switching. Journal of Systems and Software, 104:69-81, 2015.
16. N. Li, Y. Fan and Y. Liu. Reasoning about State Constraints in the Situation Calculus. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI-13), pages 997-1003, 2013.
17. Q. Yu, X. Wen and Y. Liu. Multi-agent Epistemic Explanatory Diagnosis via Reasoning about Actions. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence (IJCAI-13), pages 1183-1190, 2013.
18. L. Fang and Y. Liu. Multi-agent Knowledge and Belief Change in the Situation Calculus. In Proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI-13), pages 304-312, 2013.
19. Y. Fan, M. Cai, N. Li and Y. Liu. A first-order interpreter for knowledge-based Golog with sensing based on exact progression and limited reasoning. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence (AAAI-12), pages 734-742, ?2012.
20. Y. Liu and X. Wen. On the Progression of Knowledge in the Situation Calculus. In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence (IJCAI-11), pages 976-982, 2011.