Partitioned external-memory value iteration
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
ADT '09 Proceedings of the 1st International Conference on Algorithmic Decision Theory
Ranking policies in discrete Markov decision processes
Annals of Mathematics and Artificial Intelligence
Topological value iteration algorithms
Journal of Artificial Intelligence Research
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We establish a bound on the convergence time of the value iteration algorithm on stochastic shortest-path problems. The bound, which applies for admissible initial vectors as, for example, J\equiv 0, implies a polynomial-time convergence of value iteration for all problems with polynomially bounded \Vert{J^*}\Vert/\underline{g}. This result gives a partial answer to the open problem of bounding the convergence time of value iteration on arbitrary initial vectors. The proof is obtained by analyzing a stochastic process associated with the shortest-path problem.