# Analysis of Value Iteration Through Absolute Probability Sequences

arXiv: https://arxiv.org/abs/2502.03244 · HTML: https://mlsanity.com/paper/2502.03244/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Feb 2025.

## Built on by (most cited first, 1 of 1)

- [Beyond the Bellman Fixed Point: Geometry and Fast Policy Identification in Value Iteration](https://mlsanity.com/paper/2604.17457/) (2026)

## Abstract (arXiv)

Value Iteration is a widely used algorithm for solving Markov Decision Processes (MDPs). While previous studies have extensively analyzed its convergence properties, they primarily focus on convergence with respect to the infinity norm. In this work, we use absolute probability sequences to develop a new line of analysis and examine the algorithm's convergence in terms of the L2 norm, offering a new perspective on its behavior and performance.