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Springer Procedural Content Generation via Machine Learning - Game Development Guide

Amazon

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Description

Discover how machine learning transforms video game development through Procedural Content Generation via Machine Learning (PCGML). This Springer publication surveys current and emerging approaches to automatically generating game content-levels, quests, characters and more-by learning from existing data. Written as a beginner-focused guide, this book illustrates how PCGML is reshaping the video games industry and provides practical insights into using computers to create new game content intelligently. Whether you're a game developer, AI researcher or student exploring the intersection of machine learning and game design, this Synthesis Lectures volume offers an accessible introduction to PCGML methodologies, applications and future possibilities in modern game development.

Key Features

Springer's comprehensive survey covers current and future PCGML approaches for generating video game content through machine learning techniques.

Beginner-focused guide makes Procedural Content Generation via Machine Learning accessible to game developers new to AI applications.

Explores machine learning applications for automatically creating game levels, quests, characters and other interactive content.

Part of the Synthesis Lectures series on Games and Computational Intelligence, combining game design with advanced AI concepts.

Illustrates how PCGML is transforming the video games industry with practical examples and foundational knowledge.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
07 December 2023
Listed Since
11 November 2023

Barcode

No barcode data available

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