mlsanityData to 14 Oct 2026

Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation

arXiv 2406.10663 ↗First posted 15 Jun 2024cs.NE cs.HCcited by 1

Not on the map. Why?

Abstract (arXiv)

This paper presents an interactive platform to interpret multi-objective evolutionary algorithms. Sokoban level generation is selected as a showcase for its widespread use in procedural content generation. By balancing the emptiness and spatial diversity of Sokoban levels, we illustrate the improved two-archive algorithm, Two_Arch2, a well-known multi-objective evolutionary algorithm. Our web-based platform integrates Two_Arch2 into an interface that visually and interactively demonstrates the evolutionary process in real-time. Designed to bridge theoretical optimisation strategies with practical game generation applications, the interface is also accessible to both researchers and beginners to multi-objective evolutionary algorithms or procedural content generation on a website. Through dynamic visualisations and interactive gameplay demonstrations, this web-based platform also has potential as an educational tool.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 15 Jun 2024.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.