# Variations on the Stochastic Shortest Path Problem

arXiv: https://arxiv.org/abs/1411.0835 · HTML: https://mlsanity.com/paper/1411.0835/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Nov 2014.

## Built on by (most cited first, 3 of 3)

- [Reinforcement Learning Methods for Wordle: A POMDP/Adaptive Control Approach](https://mlsanity.com/paper/2211.10298/) (2022)
- [Convergent Reinforcement Learning Algorithms for Stochastic Shortest Path Problem](https://mlsanity.com/paper/2508.13963/) (2025)
- [Simplicity Lies in the Eye of the Beholder: A Strategic Perspective on Controllers in Reactive Synthesis](https://mlsanity.com/paper/2509.04129/) (2025)

## Abstract (arXiv)

In this invited contribution, we revisit the stochastic shortest path problem, and show how recent results allow one to improve over the classical solutions: we present algorithms to synthesize strategies with multiple guarantees on the distribution of the length of paths reaching a given target, rather than simply minimizing its expected value. The concepts and algorithms that we propose here are applications of more general results that have been obtained recently for Markov decision processes and that are described in a series of recent papers.