Level Generation with Quantum Reservoir Computing
This work applies quantum computing to game level generation, but it is incremental as it adapts an existing method to new domains.
The paper adapted a quantum reservoir computing method, originally for music generation, to create levels for Super Mario Bros and developed a real-time level generation system for a Roblox obby using superconducting qubits, investigating hardware constraints.
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.