Machine Learning Meetings and Events
Group Meetings: Group meetings are held Mondays from 11am to Noon (talk starts 11:10am) in D.L. Pratt 290C unless otherwise noted. Meetings are coordinated by Hugo Larochelle.
Tea Talks: Tea talks are held every Wednesday at 4:00pm in D.L. Pratt 290C. Talks should be simple, accessible, and not exceed 15 minutes. Speakers bring snacks, make tea, and provide a copy of the presented paper.
Group Meeting Oct 6, 2008: Hierarchical POMDP Controller Optimization by Likelihood Maximization
- Speaker: Laurent Charlin
- Abstract:
Planning problems can often be simplified by decomposing the task into smaller tasks arranged hierarchically. We recently showed that the hierarchy discovery problem can be framed as a non-convex optimization problem. However, the inherent computational difficulty of solving such an optimization problem makes it hard to scale to real-world problems. In another line of research, Marc Toussaint has developed a method to solve planning problems by maximum-likelihood estimation.
In this talk, I’ll provide a concise introduction to the field of probabilistic planning (POMDPs) and I’ll show how the hierarchy discovery problem in partially observable domains can be tackled using a similar maximum-likelihood approach. Our technique first transforms the problem into a dynamic Bayesian network through which a hierarchical structure can naturally be discovered while optimizing the policy. Experimental results demonstrate that this approach scales better than previous techniques based on non-convex optimization.
This is joint work with Marc Toussaint and Pascal Poupart.