Scaling Up: Solving POMDPs through Value Based Clustering

Yan Virin, Guy Shani, Shimony Eyal, Brafman Ronen

We present here a point-based value iteration algorithm for solving POMDPs, that orders belief state backups smartly based on a clustering of the underlying MDP states. We show our SCVI algorithm to converge faster than state of the art point-based algorithms.

Subjects: 3. Automated Reasoning; 3.4 Probabilistic Reasoning

Submitted: Apr 10, 2007

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