Learning and Optimization in Games
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2026-05-27
Tutorial by Jialin Liu (Lingnan University), Julian Togelius (New York University), and Georgios Yannakakis (University of Malta). Covers computational intelligence techniques for learning, planning, and designing in board games and video games, including evolutionary reinforcement learning, rolling horizon planning, procedural content generation, and recent advances of LLMs in games.
2026-05-27
Tutorial by Changwu Huang (SUSTech), Jialin Liu (Lingnan University), Jim Tørresen (University of Oslo), and Xin Yao (Lingnan University). Covers fairness in machine learning, explainable AI, multi-objective approaches to FairML, AI transparency, and ethical challenges in embedded systems and robotics.
2026-05-27
Tutorial by Hao Tong (Lingnan University), Jialin Liu (Lingnan University), and Xin Yao (Lingnan University). Covers CARP variants, EC-based optimization algorithms, theoretical analyses, benchmark problems, and simulation platforms for capacitated arc routing.
If you are interested, please send me your detailed CV.
If you are interested in doing a PhD with me at Lingnan University (Hong Kong SAR), there are two ways (scholarships). Note that the application submission deadline is 1 December 2024 for Hong Kong PhD Fellowship Scheme and 17 January 2025 for admission to MPhil/PhD programmes directly.
* If you are interested in working on AI in games, please take a look at our survey ``Deep Learning for Procedural Content Generation'' and the Game AI book before contacting me.
jialin.liu_AT_ln.edu.hk
