Procedural content generation in games:
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham, Switzerland
Springer
[2016]
|
| Schriftenreihe: | Computational synthesis and creative systems
|
| Schlagworte: | |
| Online-Zugang: | Cover Inhaltsverzeichnis Klappentext |
| Beschreibung: | xvi, 237 Seiten Illustrationen |
| ISBN: | 9783319427140 3319427148 |
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Datensatz im Suchindex
| _version_ | 1804176765932797952 |
|---|---|
| adam_text | Contents
1 Introduction............................................................ 1
Julian Togelius, Noor Shaker, and Mark J. Nelson
1.1 What is procedural content generation?........................ 1
1.2 Why use procedural content generation?........................... 3
1.3 Games that use PCG............................................... 4
1.4 Visions for PCG.................................................. 5
1.5 Desirable properties of a PCG solution........................... 6
1.6 A taxonomy of PCG................................................ 7
1.6.1 Online versus offline................................... 7
1.6.2 Necessary versus optional............................. 8
1.6.3 Degree and dimensions of control........................ 8
1.6.4 Generic versus adaptive................................ 8
1.6.5 Stochastic versus deterministic......................... 9
1.6.6 Constructive versus generate-and-test................... 9
1.6.7 Automatic generation versus mixed authorship........... 10
1.7 Metaphors for PCG............................................... 10
1.8 Outline of the book............................................ 12
1.9 Summary........................................................ 14
References.......................................................... 14
2 The search-based approach.............................................. 17
Julian Togelius and Noor Shaker
2.1 What is the search-based approach to procedural content
generation?................................................... 17
2.2 Evolutionary search algorithms.................................. 18
2.2.1 Other types of search algorithms....................... 20
2.3 Content representation.......................................... 20
2.4 Evaluation functions.......................................... 22
2.4.1 Direct evaluation functions.......................... 23
2.4.2 Simulation-based evaluation functions.................. 23
2.4.3 Interactive evaluation functions....................... 24
IX
X
Contents
2.5 Example: StarCraft maps....................................... 24
2.6 Example: Racing tracks........................................ 25
2.7 Example: Board game rules..................................... 26
2.8 Example: Galactic Arms Race................................... 27
2.9 Lab exercise: Evolve a dungeon............................... 27
2.10 Summary..................................................... 28
References.......................................................... 29
3 Constructive generation methods for dungeons and levels............. 31
Noor Shaker, Antonios Liapis, Julian Togelius, Ricardo Lopes, and
Rafael Bidarra
3.1 Dungeons and levels.......................................... 31
3.2 Space partitioning for dungeon generation .................... 33
3.3 Agent-based dungeon growing................................... 38
3.4 Cellular automata............................................. 42
3.5 Grammar-based dungeon generation.............................. 45
3.6 Advanced platform generation methods ......................... 47
3.7 Example applications to platform generation .................. 49
3.7.1 Spelunky.............................................. 49
3.7.2 Infinite Mario Bros................................... 51
3.8 Lab session: Level generator for InfiniTux (and Infinite Mario) ... 52
3.9 Summary....................................................... 53
References.......................................................... 54
4 Fractals, noise and agents with applications to landscapes.......... 57
Noor Shaker, Julian Togelius, and Mark J. Nelson
4.1 Terraforming and making noise................................. 57
4.1.1 Heightmaps and intensity maps......................... 58
4.2 Random terrain............................................ 59
4.2.1 Interpolated random terrain........................... 59
4.2.2 Gradient-based random terrain......................... 61
4.3 Fractal terrain............................................... 62
4.4 Agent-based landscape creation................................ 64
4.4.1 Doran and Parberry’s terrain generation............... 65
4.5 Search-based landscape generation............................. 68
4.5.1 Genetic terrain programming........................... 68
4.5.2 Simple RTS map generation............................. 69
4.6 Lab session: Generate a terrain with the diamond-square algorithm 70
4.7 Summary....................................................... 71
References.......................................................... 71
5 Grammars and L-systems with applications to vegetation and levels . 73
Julian Togelius, Noor Shaker, and Joris Dormans
5.1 Plants are everywhere......................................... 73
5.2 Grammars..................................................... 74
5.3 L-systems................................................... 75
Contents
xi
5.3.1 Graphical interpretation of L-systems............... 76
5.3.2 Bracketed L-systems.............................. 77
5.4 Evolving L-systems.......................................... 78
5.5 Generating missions and spaces with grammars................ 78
5.5.1 Graph grammars...................................... 79
5.5.2 Using graph grammars to generate missions........... 81
5.5.3 Breaking the process down into multiple generation steps 82
5.5.4 Generating spaces to accommodate a mission.......... 85
5.5.5 Extended example: ‘Dules............................ 89
5.6 Grammatical evolution for Infinite Mario Bros. level generation . . 90
5.6.1 Backus-Naur form.................................... 91
5.6.2 Grammatical evolution level generator............... 92
5.7 Lab exercise: Create plants with L-systems.................. 95
5.8 Summary..................................................... 97
References......................................................... 97
6 Rules and mechanics................................................ 99
Mark J. Nelson, Julian Togelius, Cameron Browne, and Michael Cook
6.1 Rules of the game........................................... 99
6.2 Encoding game rules.........................................100
6.3 Board games.................................................102
6.3.1 Symmetric, chess-like games.........................102
6.3.2 Balanced board games................................103
6.3.3 Evolutionary game design............................104
6.3.4 Card games ........................................ 109
6.4 Video games................................................110
6.4.1 “Automatic Game Design”: Pac-Man-like grid-world
games...............................................110
6.4.2 Sculpting rule spaces: Variations Forever...........112
6.4.3 Angelina............................................112
6.4.4 The Video Game Description Language.................116
6.4.5 Rulearn: Mixed-initiative game level creation.......117
6.4.6 Strategy games......................................117
6.4.7 The future: Better languages? Better games? 3D games? 118
6.5 Exercise: VGDL..............................................119
6.6 Summary.....................................................119
References.........................................................120
7 Planning with applications to quests and story.....................123
Yun-Gyung Cheong, Mark O. Riedl, Byung-Chull Bae, and Mark J.
Nelson
7.1 Stories in games............................................123
7.2 Procedural story generation via planning....................124
7.3 Planning as search through plan space.......................125
7.4 Domain model................................................129
7.4.1 STRIPS-style planning representation................129
Contents
xii
7.4.2 ADL, the Action Description Language..................130
7.5 Planning a story ............................................ 131
7.6 Generating game worlds and stories together....................131
7.6.1 From story to space: Game world generation............133
7.6.2 From story to time: Story plan execution..............137
7.7 Lab exercise: Write a story domain model.......................139
7.8 Summary...................................................... 140
References...........................................................140
8 ASP with applications to mazes and levels...........................143
Mark J. Nelson and Adam M. Smith
8.1 What to generate and how to generate it .......................143
8.2 Game logic and content constraints.............................144
8.3 Answer set programming.........................................145
8.4 Perfect mazes .................................................147
8.5 Playable dungeons..............................................149
8.6 Constraining the entire space of play..........................153
8.7 Exercises: Elaborations in dungeon generation..................156
8.8 Summary........................................................156
References......................................................... 157
9 Representations for search-based methods ........................... 159
Dan Ashlock, Sebastian Risi, and Julian Togelius
9.1 No generation without representation...........................159
9.2 Representing dungeons: A maze of choices.......................160
9.2.1 Notes on usage........................................162
9.3 Generating levels for a fantasy role-playing game .............162
9.3.1 Required content......................................164
9.3.2 Map generation........................................165
9.3.3 Room identification...................................165
9.3.4 Graph generation......................................166
9.3.5 Room population..................................... 166
9.3.6 Final remarks.........................................168
9.4 Generating game content with compositional pattern-producing
networks ......................................................168
9.4.1 Compositional pattern-producing networks (CPPNs) .... 168
9.4.2 Neuroevolution of augmenting topologies (NEAT).......171
9.4.3 CPPN-generated flowers in the Petalz videogame........171
9.4.4 CPPN-generated weapons in Galactic Arms Race..........172
9.5 Generating level generators....................................175
9.6 Summary ..................................................... 178
References...........................................................178
Contents
xiii
10 The experience-driven perspective.................................... 181
Noor Shaker, Julian Togelius, and Georgios N. Yannakakis
10.1 Nice to get to know you........................................181
10.2 Eliciting player experience ...................................183
10.3 Modelling player experience....................................184
10.3.1 Model input and feature extraction.....................184
10.3.2 Model output: Experience annotation....................186
10.3.3 Modelling approaches...................................187
10.4 Example: Super Mario Bros.................................... 188
10.4.1 Player experience modelling............................190
10.4.2 Grammar-based personalised level generator.............190
10.5 Lab exercise: Generate personalised levels for Super Mario Bros. . 192
10.6 Summary........................................................192
References.......................................................... 193
11 Mixed-initiative content creation.....................................195
Antonios Liapis, Gillian Smith, and Noor Shaker
11.1 Taking a step back from automation.............................195
11.2 A very short design-tool history...............................196
11.2.1 Mixed-initiative interaction...........................197
11.2.2 Computer-aided design and creativity support...........198
11.2.3 Requirements, caveats, and open problems for
mixed-initiative systems...............................199
11.2.4 Examples of CAD tools for games.................201
11.3 Interactive evolution......................;..................205
11.3.1 User fatigue and methods of combating it...............206
11.3.2 Examples of interactive evolution for games............208
11.4 Exercise.......................................................211
11.5 Summary...................................................... 212
References............................................................212
12 Evaluating content generators....................................... 215
Noor Shaker, Gillian Smith, and Georgios N. Yannakakis
12.1 I created a generator, now what?...............................215
12.2 Why is evaluation important?...................................217
12.3 Top-down evaluation via expressivity measures..................218
12.3.1 Visualizing expressive range...........................218
12.3.2 Choosing appropriate metrics ..........................220
12.3.3 Understanding controllability..........................220
12.4 Bottom-up evaluation via players...............................221
12.4.1 Which questionnaire should I use? .....................222
12.4.2 Ways around the limitations of self-reporting..........222
12.5 Summary........................................................223
References............................................................223
XIV
Contents
A Game-designer interviews......................................225
A. 1 Andrew Doull...........................................225
A.2 Ed Key.................................................228
A3 Michael Toy............................................230
A.4 Richard Evans..........................................232
A. 5 Tam Adams..............................................234
Computational Synthesis and Creative Systems
Noor Shaker • Julian Togelius • Mark J. Nelson
Procedural Content Generation in Games
This book presents the most up-to-date coverage of procedural content generation (PCG)
for games, specifically the procedural generation of levels, landscapes, items, rules,
quests, or other types of content. Each chapter explains an algorithm type or domain,
including fractal methods, grammar-based methods, search-based and evolutionary
methods, constraint-based methods, and narrative, terrain, and dungeon generation.
The authors are active academic researchers and game developers, and the book is ap-
propriate for undergraduate and graduate students of courses on games and creativity;
game developers who want to learn new methods for content generation; and researchers
in related areas of artificial intelligence and computational intelligence.
|
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| spelling | Shaker, Noor Verfasser aut Procedural content generation in games Noor Shaker, Julian Togelius, Mark J. Nelson Cham, Switzerland Springer [2016] © 2016 xvi, 237 Seiten Illustrationen txt rdacontent n rdamedia nc rdacarrier Computational synthesis and creative systems Prozedurale Generierung (DE-588)1048578739 gnd rswk-swf Computerspiel (DE-588)4010457-6 gnd rswk-swf Computerspiel (DE-588)4010457-6 s Prozedurale Generierung (DE-588)1048578739 s DE-604 Togelius, Julian Verfasser (DE-588)1166695727 aut Nelson, Mark J. Verfasser aut Erscheint auch als Online-Ausgabe 10.1007/978-3-319-42716-4 978-3-319-42716-4 DE-576;springer image/jpeg http://swbplus.bsz-bw.de/bsz478145160cov.htm 20161017135748 Cover Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029284753&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029284753&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Shaker, Noor Togelius, Julian Nelson, Mark J. Procedural content generation in games Prozedurale Generierung (DE-588)1048578739 gnd Computerspiel (DE-588)4010457-6 gnd |
| subject_GND | (DE-588)1048578739 (DE-588)4010457-6 |
| title | Procedural content generation in games |
| title_auth | Procedural content generation in games |
| title_exact_search | Procedural content generation in games |
| title_full | Procedural content generation in games Noor Shaker, Julian Togelius, Mark J. Nelson |
| title_fullStr | Procedural content generation in games Noor Shaker, Julian Togelius, Mark J. Nelson |
| title_full_unstemmed | Procedural content generation in games Noor Shaker, Julian Togelius, Mark J. Nelson |
| title_short | Procedural content generation in games |
| title_sort | procedural content generation in games |
| topic | Prozedurale Generierung (DE-588)1048578739 gnd Computerspiel (DE-588)4010457-6 gnd |
| topic_facet | Prozedurale Generierung Computerspiel |
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