Brandonnodnarb and DavidPoole: Difference between pages
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=David Poole= | |||
David is a Professor in the Department of Computer Science, University of British Columbia and the director of the Laboratory for Computational Intelligence. | |||
David's 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, and preference elicitation. | |||
In general, he is 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? David is currently working mostly on existential uncertainty, lifted inference, Semantic Science, and applications in spatial decision making, medicine and computational sustainability. He is particularly interested in probability and utility modelling, reasoning and learning over rich hypothesis spaces, with multiple possible objects with the vocabularies mediated by ontologies. | |||
http://www.cs.ubc.ca/~poole/ | |||
Latest revision as of 17:40, 24 February 2016
David Poole
David is a Professor in the Department of Computer Science, University of British Columbia and the director of the Laboratory for Computational Intelligence.
David's 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, and preference elicitation. In general, he is 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? David is currently working mostly on existential uncertainty, lifted inference, Semantic Science, and applications in spatial decision making, medicine and computational sustainability. He is particularly interested in probability and utility modelling, reasoning and learning over rich hypothesis spaces, with multiple possible objects with the vocabularies mediated by ontologies.