I am a Professor in the Department of Computer Science, University of British Columbia and the director of the Laboratory for Computational Intelligence. I was the winner of the Canadian AI Association (CAIAC), 2013 Lifetime Achievement Award. I am a Fellow of the Association for the Advancement of Artificial Intelligence, and a fellow of CAIAC. I am former chair of the Association for Uncertainty in Artificial Intelligence. During the 2014-2015 academic year, I was a Leverhulme Trust visting professor at the University of Oxford.


My main research interests are artificial intelligence, knowledge representation, reasoning under uncertainty, computational logic, diagnosis, probabilistic argumentation systems, reasoning about actions, decision theoretic planning, intelligent agents, semantic science and preference elicitation.

In general, I am interested in the questions: What should an agent do based on its beliefs, abilities and preferences? How can we acquire and efficiently use information to make better decisions? I am currently working mostly on existential uncertainty, lifted inference, Semantic Science, and applications in spatial decision making, medicine and computational sustainability. I am particularly interested in probability and utility modelling, reasoning and learning over rich hypothesis spaces, with multiple possible objects with the vocabularies mediated by ontologies.

  • long-term research overview
  • a list of all of my papers (many are on-line)
  • recent talks
  • AILog2; a simple logical representation and reasoning system with explanation facilities, declarative debugging, ask-the-user, abduction and probabilistic reasoning; formerly CILog. Some older code to play with.

For overviews of my research see: "Agents, Decisions, Beliefs, Preferences, Science and Politics" for a brief overview, "Semantic Science: Ontologies, Data and Probabilistic Theories" for a vision of what we are trying to do with semantic science, and "The Independent Choice Logic and Beyond" for an overview of what we know how to do with rich probabilistic logical relational languages, and what challenges remain. See also my listing in the International Directory of Logicians.

See also "How to write a research paper".


Statistical Relational Artificial Intelligence: Logic, Probability, and Computation, by Luc De Raedt, Kristian Kersting, Sriraam Natarajan, and David Poole, DOI: 10.2200/S00692ED1V01Y201601AIM032 Morgan & Claypool Publishers, March, 2016. This is an overview of (some of) the vast work on integrating probabilities and relational representations. You can view the video of our Statistical Relational AI tutorial at NIPS 2017.

Alan Mackworth and I wrote the textbook: Artificial Intelligence: Foundations of Computational Agents Cambridge University Press, 2010, with the second edition, 2017, now available. The full text is available online in html, and the hard copy is available from your favourite bookstore. We have a number of associated interactive learning tools in AIspace, Python implementations of most of the algorithms at AIPython.org, and some open-source interactive demos.

I am a co-author of Computational Intelligence: A Logical Approach, Oxford University Press, 1998. This is a textbook introduction to Artificial Intelligence, that presents AI from the perspective of logic (programming).

I was coeditor of: M. Fox, D. Poole, editors, Proc. Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10), Atlanta, USA, July 11 - 15, AAAI Press, 2010.

I was co-editor of Proceedings of the Tenth Annual Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann, 1994.

Teaching and Administrivia

I have lots of Interesting Pointers.

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