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.

A reproducible pipeline for extracting representative signals from wire cuts

We propose a reproducible pipeline for extracting representative signals from 2D topographic scans of the tips of cut wires. The process fully addresses many potential problems in the quality of wire cuts, including edge effects, extreme values, trends, missing values, angles, and warping. The resulting signals can be further used in source determination, which plays an important role in forensic examinations. With commonly used measurements such as the cross-correlation function, the procedure controls the false positive rate and false negative rate to the desirable values as the manual extraction pipeline but outperforms it with robustness and objectiveness.