LogAI Lab – Logic-Based Artificial Intelligence

Head: Dr. Daxin Liu (刘达欣)

E-mail: daxin[dot]liu[at]nju.edu.cn

Office Hour:  No fixed, by appointment

Short Bio

Currently, Dr. Daxin Liu is an associate professor at Nanjing University, an awardee of National High-Level Youth Talent Program (Overseas) 国家级高层次青年人才(海外). Before joining in Nanjing University as an assistant professor (2024-2025), he was a postdoctoral researcher (2023-2024) at the University of Edinburgh (supervised by Dr. Vaishak Belle) in AIAI, a doctoral researcher (2018-2022) at the RWTH-Aachen university (2018-2022) supervised by Prof. Gerhard Lakemeyer. During that time, he was affiliated with the Knowledge-Based Systems Group and the UnRAVeL Research Training Group. He obtained the Master degree in Computer Science (2018) in Nanjing University and Bachelor degree in Software Engineering (2015) in Central South University.

Research Interest

Briefly, Artificial Intelligence, Knowledge Representation,Cognitive Robotics, Program Verification


The LogAI Lab explores logical and formal methods at the heart of artificial intelligence. We focus on knowledge representation, reasoning, and the integration of symbolic logic with machine learning. Our research covers topics such as actions and causality, knowledge and belief, probability, planning, synthesis, and verification. Most of our work is theoretical, grounded in logic and formal systems, aimed at building interpretable and robust AI. See our latest publications for current research directions.

Project

• 基于行动推理的可靠决策系统关键技术（国家自然科学基金青年科学基金项目, 2026.1 - 2028.12, 主持）
  Key Technologies for Reliable Decision-Making Systems Based on Reasoning about Actions (NSFC Grant No. 6250071156)

Message for propsective students

The lab is expanding, we are looking for prospective (bachelor/master/doctoral) students who are interested in the above research area. If you are interested, why no send us an email.

Community Service

Served as PC members for conference: AAAI 2023-2026; AAMAS 2025,2026; ECAI 2023,2024; KR 2024; PRICAI 2025; ISWC 2025
Served as reviewers for journal: Trans. on Comput. Logic
Served as guest editor for journal: Neurosymbolic AI

Selected Recent Publications

          Daxin Liu, Vaishak Belle.
          Epistemic Modal Logic Meets Algebraic Model Counting
          In proceeding of the 25nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2026 (accepted to appear).

          Daxin Liu, Gerhard Lakemeyer.
          A Framework for Belief-based Programs and Their Verification
          Journal of Artificial Intelligence Research (JAIR), 2025.

          Daxin Liu, Vaishak Belle.
          What Is a Counterfactual Cause in Action Theories?
          In proceeding of the 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2025.

          Daxin Liu, Jens Claβen
          On Action Theories with Iterable First-Order Progression
          In proceeding of the 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025.

          Daxin Liu, Jens Claβen
          First-Order Progression beyond Local-Effect and Normal Actions
          In proceeding of the 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024.


A full list is here. Find them at DBLP

Teaching

   Nanjing University

Advanced Algebra II [SS 2025]

   RWTH Aachen University

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]

   Nanjing University

Graph Theory [WS 2017/2018]

Recommemded Books and Papers

For reasoning about knowledge and belief:

[1] Levesque, Hector J., and Gerhard Lakemeyer. The logic of knowledge bases (2ed). MIT Press, 2022.
[2] Fagin, Ronald, Joseph Y. Halpern, Yoram Moses, and Moshe Vardi. Reasoning about knowledge. MIT Press, 2004.
The book [1] is a modal treatment of knowledge and more up to date while the book [2] is more classical.

For reasoning about actions and causality:

[3] Reiter, Raymond. Knowledge in action: logical foundations for specifying and implementing dynamical systems. MIT Press, 2001.
[4] Halpern, Joseph Y. Actual causality. MIT Press, 2016.
[3] is the Reiter's reconsideration of the situation calculus and [4] is the latest book about HP account of actual causality.

For reasoning about probability and uncertainty:

[5] Pearl, Judea. Probabilistic reasoning in intelligent systems: networks of plausible inference. Elsevier, 2014.
[6] Bacchus, Fahiem, Joseph Y. Halpern, and Hector J. Levesque. Reasoning about noisy sensors and effectors in the situation calculus. Artificial Intelligence (1999).
[5] is the famous book on reasoning about probability and [6] provides a logical treatment of probability.

For verification and model-checking:

[7] Baier, Christel, and Joost-Pieter Katoen. Principles of model checking. MIT Press, 2008.

The above books and papers shaped my knowledge of KR, but, of course this is purely subjective and non-exhaustive.