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The Value Iteration Algorithm is Not Strongly Polynomial for Discounted Dynamic Programming

This note provides a simple example demonstrating that, if exact computations are allowed, the number of iterations required for the value iteration algorithm to find an optimal policy for discounted dynamic programming problems may grow arbitrarily quickly with the size of the problem. In particular, the number of iterations can be exponential in the number of actions. Thus, unlike policy iterations, the value iteration algorithm is not strongly polynomial for discounted dynamic programming.

preprint2013arXivOpen access
Eugene A. FeinbergJefferson Huang
math.OCArtificial Intelligence
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Eugene A. FeinbergJefferson Huang

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