Level Generation with Quantum Reservoir Computing
Not on the map. Why?
Abstract (arXiv)
Reservoir computing is a form of machine learning particularly suited for time series analysis, including forecasting predictions. We take an implementation of quantum reservoir computing that was initially designed to generate variants of musical scores and adapt it to create levels of Super Mario Bros. Motivated by our analysis of these levels, we develop a new Roblox textitobby where the courses can be generated in real time on superconducting qubit hardware, and investigate some of the constraints placed by such real-time generation.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 8 of its 28 references that are in the map. First posted on arXiv 19 May 2025.
Builds on
8 of 28 references.
References · 8
- 2023Challenges and Opportunities in Quantum Optimizationcited by 42
- 2019Bootstrapping Conditional GANs for Video Game Level Generationcited by 35
- 2021Generating and Blending Game Levels via Quality-Diversity in the Latent Space of a Variational Autoencodercited by 27
- 2022Quantum Natural Language Generation on Near-Term Devicescited by 11
- 2020A quantum procedure for map generationcited by 4
- 2019Reservoir Computing based on Quenched Chaoscited by 1
- 2022Defining Quantum Gamescited by 1
- 2025Level Generation with Constrained Expressive Rangecited by 1
Built on by
Not cited yet.