English

Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation

Neural and Evolutionary Computing 2024-06-18 v1 Human-Computer Interaction

Abstract

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.

Cite

@article{arxiv.2406.10663,
  title  = {Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation},
  author = {Qingquan Zhang and Yuchen Li and Yuhang Lin and Handing Wang and Jialin Liu},
  journal= {arXiv preprint arXiv:2406.10663},
  year   = {2024}
}
R2 v1 2026-06-28T17:07:17.525Z