An Integrated Framework for AI Assisted Level Design in 2D Platformers
This addresses the challenge of creating fun and challenging levels for game designers, but it appears incremental as it builds on existing AI-assisted design concepts.
The paper tackles the problem of designing video game levels for 2D platformers by presenting an integrated framework that assists designers with tools for creation, difficulty estimation of jumps, and level evaluation metrics, validated through experiments with human players.
The design of video game levels is a complex and critical task. Levels need to elicit fun and challenge while avoiding frustration at all costs. In this paper, we present a framework to assist designers in the creation of levels for 2D platformers. Our framework provides designers with a toolbox (i) to create 2D platformer levels, (ii) to estimate the difficulty and probability of success of single jump actions (the main mechanics of platformer games), and (iii) a set of metrics to evaluate the difficulty and probability of completion of entire levels. At the end, we present the results of a set of experiments we carried out with human players to validate the metrics included in our framework.