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Book Synopsis

Introduction.- Classical PCG.- An Introduction of ML Through PCG.- PCGML Process Overview.- Constraint-based PCGML Approaches.- Probabilistic PCGML Approaches.- Neural Networks Introduction.- Sequence-based DNN PCGML.- Grid-based DNN PCGML.- Reinforcement Learning PCG.- Generative AI.- Mixed-Initiative PCGML.- Open Problems.- Resources and Conclusions.

Procedural Content Generation via Machine Learning

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    A Hardback by Matthew Guzdial

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      View other formats and editions of Procedural Content Generation via Machine Learning by Matthew Guzdial

      Publisher: Springer
      Publication Date: 22/07/2025
      ISBN13: 9783031847554, 978-3031847554
      ISBN10:
      Also in:
      Machine learning

      Description

      Book Synopsis

      Introduction.- Classical PCG.- An Introduction of ML Through PCG.- PCGML Process Overview.- Constraint-based PCGML Approaches.- Probabilistic PCGML Approaches.- Neural Networks Introduction.- Sequence-based DNN PCGML.- Grid-based DNN PCGML.- Reinforcement Learning PCG.- Generative AI.- Mixed-Initiative PCGML.- Open Problems.- Resources and Conclusions.

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