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      Exploring Minecraft Settlement Generators with Generative Shift Analysis

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          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.

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          Author and article information

          Journal
          11 September 2023
          Article
          2309.05371
          2f052c84-b2a2-4b09-9bc8-d75c0a34c425

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          cs.AI

          Artificial intelligence
          Artificial intelligence

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