mlsanityData to 7 Oct 2026

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

arXiv 1312.6832 ↗First posted 19 Dec 2013cs.AI math.OCcited by 4

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Abstract (arXiv)

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.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Dec 2013.

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4 papers.