Exploring Minecraft Settlement Generators with Generative Shift Analysis
Hervé, Jean-Baptiste, Withington, Oliver, Hervé, Marion, Tokarchuk, Laurissa, Salge, Christoph
–arXiv.org Artificial Intelligence
With growing interest in Procedural Content Generation (PCG) it becomes increasingly important to develop methods and tools for evaluating and comparing alternative systems. There is a particular lack regarding the evaluation of generative pipelines, where a set of generative systems work in series to make iterative changes to an artifact. We introduce a novel method called Generative Shift for evaluating the impact of individual stages in a PCG pipeline by quantifying the impact that a generative process has when it is applied to a pre-existing artifact. We explore this technique by applying it to a very rich dataset of Minecraft game maps produced by a set of alternative settlement generators developed as part of the Generative Design in Minecraft Competition (GDMC), all of which are designed to produce appropriate settlements for a pre-existing map. While this is an early exploration of this technique we find it to be a promising lens to apply to PCG evaluation, and we are optimistic about the potential of Generative Shift to be a domain-agnostic method for evaluating generative pipelines.
arXiv.org Artificial Intelligence
Sep-11-2023
- Country:
- Europe > United Kingdom > England > Hertfordshire (0.14)
- Genre:
- Research Report > Promising Solution (0.66)
- Industry:
- Leisure & Entertainment > Games > Computer Games (1.00)
- Technology: