Probabalistic Inference for solving (PO)MDPs
- π€ Speaker: Finale Doshi (University of Cambridge)
- π Date & Time: Thursday 15 January 2009, 14:00 - 15:30
- π Venue: Engineering Department, CBL Room 438
Abstract
Recent work has shown that finding a near-optimal policy in an MDP or POMDP can be framed as an inference problem. We will focus on:
“Probabilistic inference for solving (PO)MDPs,” Toussaint et. al. (2006)
and perhaps talk a little bit about:
“Hierarchical POMDP Controller Optimization by Likelihood Maximization,” Toussaint et. al. (2008)
and discuss implications for planning and reinforcement learning.
Series This talk is part of the Machine Learning Reading Group @ CUED series.
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Thursday 15 January 2009, 14:00-15:30