Exploring Minecraft Settlement Generators with Generative Shift Analysis

09/11/2023
by   Jean-Baptiste Hervé, et al.
0

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.

READ FULL TEXT

page 6

page 7

research
05/30/2022

Compressing and Comparing the Generative Spaces of Procedural Content Generators

The past decade has seen a rapid increase in the level of research inter...
research
10/31/2022

Visualising Generative Spaces Using Convolutional Neural Network Embeddings

As academic interest in procedural content generation (PCG) for games ha...
research
07/12/2020

Tabletop Roleplaying Games as Procedural Content Generators

Tabletop roleplaying games (TTRPGs) and procedural content generators ca...
research
09/19/2023

Believable Minecraft Settlements by Means of Decentralised Iterative Planning

Procedural city generation that focuses on believability and adaptabilit...
research
04/20/2023

Using Text-to-Image Generation for Architectural Design Ideation

The recent progress of text-to-image generation has been recognized in a...
research
07/05/2021

Exploring Data Pipelines through the Process Lens: a Reference Model forComputer Vision

Researchers have identified datasets used for training computer vision (...
research
12/21/2022

Not Just Pretty Pictures: Text-to-Image Generators Enable Interpretable Interventions for Robust Representations

Neural image classifiers are known to undergo severe performance degrada...

Please sign up or login with your details

Forgot password? Click here to reset