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001 978-3-031-16719-5
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020 _a9783031167195
_9978-3-031-16719-5
024 7 _a10.1007/978-3-031-16719-5
_2doi
050 4 _aQ325.5-.7
072 7 _aUYQM
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aUYQM
_2thema
082 0 4 _a006.31
_223
100 1 _aGuzdial, Matthew.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979974
245 1 0 _aProcedural Content Generation via Machine Learning
_h[electronic resource] :
_bAn Overview /
_cby Matthew Guzdial, Sam Snodgrass, Adam J. Summerville.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXIII, 238 p. 82 illus., 63 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Games and Computational Intelligence,
_x2573-6493
505 0 _aIntroduction -- 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 -- Mixed-Initiative PCGML -- Open Problems -- Resource and Conclusions.
520 _aThis book surveys current and future approaches to generating video game content with machine learning or Procedural Content Generation via Machine Learning (PCGML). Machine learning is having a major impact on many industries, including the video game industry. PCGML addresses the use of computers to generate new types of content for video games (game levels, quests, characters, etc.) by learning from existing content. The authors illustrate how PCGML is poised to transform the video games industry and provide the first ever beginner-focused guide to PCGML. This book features an accessible introduction to machine learning topics, and readers will gain a broad understanding of currently employed PCGML approaches in academia and industry. The authors provide guidance on how best to set up a PCGML project and identify open problems appropriate for a research project or thesis. This book is written with machine learning and games novices in mind and includes discussions of practical and ethical considerations along with resources and guidance for starting a new PCGML project.
650 0 _aMachine learning.
_91831
650 0 _aComputer games
_xProgramming.
_96563
650 0 _aArtificial intelligence.
_93407
650 0 _aComputational intelligence.
_97716
650 0 _aComputer science.
_99832
650 1 4 _aMachine Learning.
_91831
650 2 4 _aGame Development.
_949481
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aComputational Intelligence.
_97716
650 2 4 _aComputer Science.
_99832
700 1 _aSnodgrass, Sam.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979975
700 1 _aSummerville, Adam J.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_979976
710 2 _aSpringerLink (Online service)
_979977
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031167188
776 0 8 _iPrinted edition:
_z9783031167201
776 0 8 _iPrinted edition:
_z9783031167218
830 0 _aSynthesis Lectures on Games and Computational Intelligence,
_x2573-6493
_979978
856 4 0 _uhttps://doi.org/10.1007/978-3-031-16719-5
912 _aZDB-2-SXSC
942 _cEBK
999 _c84880
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