Jul 11, 2012 · Abstract:We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes.

We present a major improvement to the incre- mental pruning algorithm for solving partially observable Markov decision processes. Our tech-.

We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes. Our technique targets the ...

We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes. Our technique targets the ...

We present a major improvement to the incremental pruning algorithm for solving partially observable Markov decision processes. Our technique targets the ...

It is found that incremental pruning is presently the most efficient exact method for solving POMDPS. Most exact algorithms for general partially observable ...

Bibliographic details on Region-Based Incremental Pruning for POMDPs.

Region-based incre- mental pruning for POMDPs. In Proceedings of the 20th. Conference on Uncertainty in Artificial Intelligence, 146–. 153. Hansen, E. A. 1998.

A major improvement to the dynamic programming (DP) algorithm for solving partially observable Markov decision processes (POMDPs) is presented, showing that ...

In par- ticular, incremental pruning is currently considered the most efficient exact algorithm for performing the dynamic programming update for POMDPs. Most ...