Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation
<|reference_start|>Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation: 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.<|reference_end|>
@article{zhang2024interpreting,
    title={Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level
  Generation},
    author={Qingquan Zhang, Yuchen Li, Yuhang Lin, Handing Wang, Jialin Liu},
    journal={arXiv preprint arXiv:2406.10663},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.10663},
    primaryClass={cs.NE cs.HC}
}