# Gamifying the Vehicle Routing Problem with Stochastic Requests

arXiv: https://arxiv.org/abs/1911.05922 · HTML: https://mlsanity.com/paper/1911.05922/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Nov 2019.

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

- [Press Start to Charge: Videogaming the Online Centralized Charging Scheduling Problem](https://mlsanity.com/paper/2601.12543/) (2026)

## Abstract (arXiv)

Do you remember your first video game console? We remember ours. Decades ago, they provided hours of entertainment. Now, we have repurposed them to solve dynamic and stochastic optimization problems. With deep reinforcement learning methods posting superhuman performance on a wide range of Atari games, we consider the task of representing a classic logistics problem as a game. Then, we train agents to play it. We consider several game designs for the vehicle routing problem with stochastic requests. We show how various design features impact agents' performance, including perspective, field of view, and minimaps. With the right game design, general purpose Atari agents outperform optimization-based benchmarks, especially as problem size grows. Our work points to the representation of dynamic and stochastic optimization problems via games as a promising research direction.