Level Generation with Quantum Reservoir Computing

TL;DR

This paper adapts quantum reservoir computing, originally used for music generation, to procedurally generate Super Mario Bros. levels and explores real-time level creation on quantum hardware.

Contribution

It introduces a novel application of quantum reservoir computing for game level generation and discusses real-time implementation constraints on quantum hardware.

Findings

Successful adaptation of quantum reservoir computing for level generation

Development of a Roblox obby with real-time course generation

Analysis of quantum hardware constraints for real-time applications

Abstract

Reservoir computing is a form of machine learning particularly suited for time series analysis, including forecasting predictions. We take an implementation of \emph{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 \textit{obby} 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.