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Kee Siong Ng,
a Malaysian computer scientist and adjunct research fellow at College of Engineering and Computer Science, Australian National University. His research interests covers symbolic or knowledge-based machine learning, functional and logic programming paradigms, Universal reinforcement learning including a joint attempt with Joel Veness, Marcus Hutter and David Silver at approximating an AIXI agent.

Selected Publications

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• Kee Siong Ng (2001). Neural Networks for Structured Data. BSc-Thesis, zipped ps
• Kee Siong Ng (2005). Learning Comprehensible Theories from Structured Data. PhD-Thesis, pdf
• Kee Siong Ng, John Lloyd, William Uther (2008). Probabilistic modelling, inference and learning using logical theories. pdf
• Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver (2009). A Monte Carlo AIXI Approximation, pdf
• Joel Veness, Kee Siong Ng, Marcus Hutter, David Silver (2010). Reinforcement Learning via AIXI Approximation. Association for the Advancement of Artificial Intelligence (AAAI), pdf
• John Lloyd, Kee Siong Ng (2010). Declarative Programming for Agent Applications. pdf

External Links

• Kee Siong Ng from Microsoft Academic Search

References

1. ^ Kee Siong's Homepage
2. ^ Kee Siong Ng from Microsoft Academic Search

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