000 | 03789nam a22005895i 4500 | ||
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001 | 978-3-031-16719-5 | ||
003 | DE-He213 | ||
005 | 20240730163704.0 | ||
007 | cr nn 008mamaa | ||
008 | 221206s2022 sz | s |||| 0|eng d | ||
020 |
_a9783031167195 _9978-3-031-16719-5 |
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024 | 7 |
_a10.1007/978-3-031-16719-5 _2doi |
|
050 | 4 | _aQ325.5-.7 | |
072 | 7 |
_aUYQM _2bicssc |
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_aMAT029000 _2bisacsh |
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_aUYQM _2thema |
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_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 |
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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 |
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