Exploring Minecraft Settlement Generators with Generative Shift Analysis

TL;DR

This paper introduces Generative Shift, a new evaluation method for procedural content generation pipelines, demonstrated on Minecraft settlement generators, offering a promising domain-agnostic approach for assessing iterative generative systems.

Contribution

The paper presents Generative Shift, a novel technique for evaluating individual stages in generative pipelines, applied to Minecraft settlement generators to demonstrate its potential.

Findings

Generative Shift effectively quantifies the impact of generative stages.

Applied to Minecraft maps, it reveals differences between settlement generators.

The method shows promise as a domain-agnostic evaluation tool.

Abstract

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.