E-mail: daxin.liu[at]ed.ac.uk
Office Hour: No fixed, by appointment
Currently, I am a postdoctoral researcher at the University of Edinburgh funded by the Royal Society University Research Fellowship working with Dr. Vaishak Belle. Previously, I was a doctoral researcher (2018-2022)
at the RWTH-Aachen university, under the supervision of Prof.Gerhard Lakemeyer
in the Department of Computer Science. During that time, I was affiliated with the Knowledge-Based Systems Group and
the UnRAVeL Research Training Group. I finished my Master in Computer Science
(2018) in Nanjing University and Bachelor in Software Engineering (2015) in Central South University.
Daxin Liu, Vaishak Belle.
Progression with Probabilities in the Situation Calculus: Representation and Succinctness.
In proceeding of the 23nd International Conference on Autonomous Agents and Multiagent Systems(AAMAS), 2024. (X2A)
Daxin Liu, Qinfei Huang, Vaishak Belle, Gerhard Lakemeyer.
Verifying Belief-based Programs via Symbolic Dynamic Programming.
In proceeding of 26th European Conference on Artificial Intelligence(ECAI) 2023
Daxin Liu, Qihui Feng, Vaishak Belle, Gerhard Lakemeyer.
Concerning Measures in a First-order Logic with Actions and Meta-beliefs.
In proceeding of 20th International Conference on Principles of Knowledge Representation and Reasoning(KR), 2023
Daxin Liu, Qihui Feng.
On the Progression of Belief.
Artificial Intelligence Journal(AIJ), 2023
Qihui Feng, Daxin Liu, Vaishak Belle, Gerhard Lakemeyer.
A Logic of Only-Believing over Arbitrary Probability Distributions.
In proceeding of the 22nd International Conference on Autonomous Agents and Multiagent Systems(AAMAS), 2023.
Daxin Liu, Gerhard Lakemeyer.
On the Verification of Belief Programs.
http://arxiv.org/abs/2204.12562,2022.
Daxin Liu, Qihui Feng.
On the Progression of Belief.
In proceeding of 18th International Conference on Principles of Knowledge Representation and Reasoning(KR), (Best Student Paper), 2021.
Daxin Liu, Gerhard Lakemeyer.
Reasoning about Beliefs and Meta-Beliefs by Regression in an Expressive Probabilistic Action Logic.
In proceeding of the 30th International Joint Conference on Artificial Intelligence(IJCAI), 2021.
Daxin Liu, Gong Cheng, Qingxia Liu, Yuzhong Qu.
Fast and Practical Snippet Generation for RDF Datasets.
ACM Transactions on the Web(TWEB), 13(4):19, 2019.
Gong Cheng, Daxin Liu, Yuzhong Qu.
Fast Algorithms for Semantic Association Search and Pattern Mining.
IEEE Transactions on Knowledge and Data Engineering(TKDE), 2019.
Yu Gu, Yue Liang,Gong Cheng, Daxin Liu, Ruidi Wei, Yuzhong Qu.
Diversified and Verbalized Result Summarization for Semantic Association Search.
International Conference on Web Information Systems Engineering(WISE), 381-390, 2018
Gong Cheng, Daxin Liu, Yuzhong Qu.
Efficient algorithms for association finding and frequent association pattern mining.
International Semantic Web Conference(ISWC), 119-134, 2016
Introduction to Artificial Intelligence [WS 2021/2022]
Introduction to Artificial Intelligence [WS 2020/2021]
Introduction to Knowledge Representation [SS 2020]
Introduction to Artificial Intelligence [WS 2019/2020]
Seminar: Selected Topics in Agent Behavior Modeling [SS 2019]
Lab Course: Flexible Task-Level Reasoning and Execution for Logistics Robots [WS 2018/2019]
Graph Theory [WS 2017/2018]