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• Inference in Probabilistic Graphical Models : Modelling constraints in Bayesian Networks using conditioned nodes. Unexpected biases can arise in the joint distribution if this is done naively without considering the way inference is performed. I showed a way to shield part of the BN from this bias while maintaining the constraint. (M.Sc. Thesis 2005, CAI2007)
• Reinforcement Learning : My recent research falls under the general category of Reinforcement Learning. There is a lot of exciting research happening in this field lately with the growing power of PAC-MDP algorithms.
• My algorithm, EPG…I proposed using equilibrium policies as a representation for policies in large spatiotemporal planning problems and demonstrated how they could be used to perform policy gradient planning. (AAAI2011, Ph.D. Thesis 2011)
• I used forestry planning as my demonstration problem. I looked at the management of forest ecosystems under spatial constraints and under the presence of stochastic spatial disturbances moving across the landscape such as Mountain Pine Beetles. (UAI2009, Ph.D. Thesis)