刘咏梅，bat365在线中国登录入口教授，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。研究方向为人工智能，知识表示与推理，自然语言处理，智能规划。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！
目前正在开展的研究工作：
1.自然语言上的综合逻辑推理：对自然语言进行理解需要各种逻辑推理能力，如演绎推理，对动作和变化，知识和信念，时间和空间进行推理的能力。我们关注如何有效地将知识表示与推理的传统理论和方法与基于大语言模型的自然语言处理技术相结合。
2.通用规划（generalized planning）及其应用：规划能力是人类智能的一种关键能力。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通解。通用规划关注的是自动规划中的通用智能，和程序自动生成密切相关。
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。
人工智能，知识表示与推理，自然语言处理，智能规划
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
2007年12月至今，bat365官方网站登录，教授，博士生导师
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
1. 国家自然科学基金项目， 基于逻辑程序设计的自然语言上的综合逻辑推理的神经符号方法
2. 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
3. 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
4. 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
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
DBLP链接：https://dblp.org/pid/73/4188-1.html
• Weinan He, Canming Huang, Zhanhao Xiao, Yongmei Liu: Exploring the Capacity of Pretrained Language Models for Reasoning about Actions and Change. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023), 2023
• Zhenhe Cui, Weidu Kuang, Yongmei Liu: Automatic Verification for Soundness of Bounded QNP Abstractions for Generalized Planning. In Proceedings of the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), 2023
• Aiting Liang, Yongmei Liu: A Model-Theoretic Approach to Belief Revision in Multi-Agent Belief Logic and Its Syntactic Characterizations. In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), 2023
• Zhaoshuai Liu, Aiting Liang, Yongmei Liu: Epistemic JAADL: A Modal Logic for Joint Abilities with Imperfect Information. In Proceedings of the 26th European Conference on Artificial Intelligence, (ECAI 2023), 2023
• H. Zeng, Y. Liang ad Y. Liu. A Native Qualitative Numeric Planning Solver Based on AND/OR Graph Search. In Proceedings of the Thirty-first International Joint Conference on Artificial Intelligence (IJCAI-22), 2022.
• S. Ou and Y. Liu. Learning to Generate Programs for Table Fact Verification via Structure-Aware Semantic Parsing. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL-2022), 2022
• Y. Xiu, Z. Xiao and Y. Liu. LogicNMR: Probing the Non-monotonic Reasoning Ability of Pre-trained Language Models. In Proceedings of The 2022 Conference on Empirical Methods in Natural Language Processing (Findings) (EMNLP-2022), 2022
• K. Luo and Y. Liu. Automated Synthesis of Generalized Invariant Strategies via Counterexample-Guided Strategy Refinement. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22), 2022.
• W. He, C. Huang, Y. Liu and X. Zhu. WINOLOGIC: A Zero-Shot Logic-based Diagnostic Dataset for Winograd Schema Challenge. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing(EMNLP-2021), 2021
• C. Huang, W. He and Y. Liu. Improving Unsupervised Commonsense Reasoning Using Knowledge-Enabled Natural Language Inference. In Proceedings of The 2021 Conference on Empirical Methods in Natural Language Processing (Findings) (EMNLP-2021), 2021
• H. Wan, B. Fang and Y. Liu. A General Multi-agent Epistemic Planner Based on Higher-order Belief Change. Artificial Intelligence 301 (2021) 103562.
• Z. Cui, Y. Liu and K. Luo. A Uniform Abstraction Framework for Generalized Planning. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence (IJCAI-21), 2021.
• 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.
• 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.
• 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.
• 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.
• L. Fang, Y. Liu and H. van Ditmarsch. Forgetting in multi-agent modal logics. Artificial Intelligence, 266: 51-80, 2019.
• 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.
• 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.
• 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.
• 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.
• L. 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.
• 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.
• 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.
• 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.
• 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.
• X. Wang and Y. Liu. Automated fault localization via hierarchical multiple predicate switching. Journal of Systems and Software, 104:69-81, 2015.