Scholarlink

This book focuses on Procedural Content Generation via Machine Learning (PCGML), the generation of media or content with machine learning techniques Summerville et al. (2018b). While machine learning (ML) has been used to generate a wide variety of content including visual art, music, and stories, PCGML (and this book) focus largely on video games. Therefore, we focus on the types of content specific to video games, such as levels, mechanics, game character art, sound effects, game narrative, and so forth. Video games are a difficult medium for ML, due to their complexity and lack of training data as we’ll discuss further below. But this difficulty is part of what makes the problems in this field so compelling.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Introduction

  • 章节

  • 发表日期：

    2025年

查看全文
  • Matthew Guzdial,
  • Sam Snodgrass,
  • Adam Summerville

摘要

This book focuses on Procedural Content Generation via Machine Learning (PCGML), the generation of media or content with machine learning techniques Summerville et al. (2018b). While machine learning (ML) has been used to generate a wide variety of content including visual art, music, and stories, PCGML (and this book) focus largely on video games. Therefore, we focus on the types of content specific to video games, such as levels, mechanics, game character art, sound effects, game narrative, and so forth. Video games are a difficult medium for ML, due to their complexity and lack of training data as we’ll discuss further below. But this difficulty is part of what makes the problems in this field so compelling.