Mechanizing Exploratory Game Design - Adam Smith

327 Pages·2013·4.09 MB·English

by  Adam M. Smith

Mechanizing Exploratory Game Design
Adam M. Smith
Copyright (cid:13)c 2012 Adam M. Smith
1 Introduction 1
2 Interdisciplinary Context & Motivations 13
3 Game Design 15
4 Design Studies 37
5 Computational Creativity 49
6 Symbolic AI 61
7 Synthesis of Goals 83
8 Mechanizing Appositional Reasoning 87
9 Computational Caricature 101
10 ASP for Design Automation 115
11 Applied Systems Overview 173
12 Ludocore 175
13 Biped 191
14 Variations Forever 207
15 Refraction Tools 223
16 Rational Curiosity 245
17 Evaluation 261
18 Conclusion 279
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iv
Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . xiv
1 Introduction 1
1.1 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1.1 Amplify creativity of human game designers . . . . 3
1.1.2 Support deep, play-time design automation . . . . 3
1.1.3 Demonstrate tools that respect design problems. . 4
1.2 Research Context . . . . . . . . . . . . . . . . . . . . . . . 4
1.2.1 Game Design . . . . . . . . . . . . . . . . . . . . . 4
1.2.2 Design Studies . . . . . . . . . . . . . . . . . . . . 5
1.2.3 Computational Creativity . . . . . . . . . . . . . . 5
1.2.4 Symbolic AI. . . . . . . . . . . . . . . . . . . . . . 6
1.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3.1 Mechanizing Design Spaces . . . . . . . . . . . . . 7
1.3.2 Situating Mechanized Design . . . . . . . . . . . . 8
1.4 Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
1.4.1 Design Spaces . . . . . . . . . . . . . . . . . . . . . 10
1.4.2 Computational Caricature . . . . . . . . . . . . . . 10
1.4.3 Target Audience: Procedurally Literate Designer-
Programmers . . . . . . . . . . . . . . . . . . . . . 10
1.4.4 Automating Logical Reasoning . . . . . . . . . . . 11
1.4.5 Artifacts as Communication . . . . . . . . . . . . . 11
1.5 Outline of Dissertation . . . . . . . . . . . . . . . . . . . . 11
2 Interdisciplinary Context & Motivations 13
3 Game Design 15
3.1 Best Practices . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.1.1 Prototyping . . . . . . . . . . . . . . . . . . . . . . 16
3.1.2 Playtesting . . . . . . . . . . . . . . . . . . . . . . 18
3.1.3 Balancing . . . . . . . . . . . . . . . . . . . . . . . 20
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3.2 Folk Psychology in Game Design . . . . . . . . . . . . . . 21
3.3 Call for Structure . . . . . . . . . . . . . . . . . . . . . . . 22
3.4 Procedural Content Generation . . . . . . . . . . . . . . . 25
3.4.1 PCG Meets Game Design . . . . . . . . . . . . . . 26
3.4.2 Typical Architectures for Content Generators . . . 28
3.5 Attempts at Formalization and Automation . . . . . . . . 30
3.5.1 MDA . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.5.2 A Factoring of the Concerns in Game Design . . . 31
3.5.3 Ludi . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.5.4 A Generic Framework . . . . . . . . . . . . . . . . 33
3.6 Game Design as a Design Discipline . . . . . . . . . . . . 34
4 Design Studies 37
4.1 The Relationship between Science and Design . . . . . . . 38
4.2 Methods of Design Studies . . . . . . . . . . . . . . . . . . 39
4.3 Vocabulary of Design . . . . . . . . . . . . . . . . . . . . . 40
4.3.1 Glossary . . . . . . . . . . . . . . . . . . . . . . . . 44
4.4 The Automated Architect . . . . . . . . . . . . . . . . . . 45
5 Computational Creativity 49
5.1 Vocabulary of Creativity . . . . . . . . . . . . . . . . . . . 50
5.1.1 “Creativity”. . . . . . . . . . . . . . . . . . . . . . 50
5.1.2 Novelty, Value, and Surprise. . . . . . . . . . . . . 50
5.1.3 Process vs. Product vs. Producer. . . . . . . . . . 52
5.1.4 Combinational, Exploratory, and Transformational
Creativity . . . . . . . . . . . . . . . . . . . . . . . 52
5.1.5 Closed Loops . . . . . . . . . . . . . . . . . . . . . 54
5.2 Computational Creativity Meets Game Design . . . . . . 56
5.3 Mechanization and Computational Creativity . . . . . . . 57
6 Symbolic AI 61
6.1 Logic Programming . . . . . . . . . . . . . . . . . . . . . 62
6.1.1 Deductive Logic Programming . . . . . . . . . . . 64
6.1.2 Inductive Logic Programming . . . . . . . . . . . . 65
6.1.3 Abductive Logic Programming . . . . . . . . . . . 66
6.1.4 Prolog . . . . . . . . . . . . . . . . . . . . . . . . . 67
6.1.5 Constraint Logic Programming . . . . . . . . . . . 68
6.1.6 Answer Set Programming . . . . . . . . . . . . . . 69
6.2 Standard Problems . . . . . . . . . . . . . . . . . . . . . . 70
6.3 Standard Solutions . . . . . . . . . . . . . . . . . . . . . . 72
6.3.1 Backtracking and Completeness . . . . . . . . . . . 72
6.3.2 Heuristics . . . . . . . . . . . . . . . . . . . . . . . 73
6.3.3 Consistency and Propagation . . . . . . . . . . . . 74
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6.3.4 Constraint Learning . . . . . . . . . . . . . . . . . 74
6.3.5 Randomness and Restarts . . . . . . . . . . . . . . 75
6.4 General Game Playing . . . . . . . . . . . . . . . . . . . . 76
6.4.1 History . . . . . . . . . . . . . . . . . . . . . . . . 77
6.4.2 Rule Representations. . . . . . . . . . . . . . . . . 77
6.4.3 General Game Playing vs. Action Planning . . . . 79
6.5 Super-symbolic AI: The Knowledge Level . . . . . . . . . 81
7 Synthesis of Goals 83
8 Mechanizing Appositional Reasoning 87
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 87
8.2 Appositional and Abductive Reasoning . . . . . . . . . . . 88
8.3 Design Spaces . . . . . . . . . . . . . . . . . . . . . . . . . 90
8.4 Requirements for Knowledge Representations . . . . . . . 91
8.4.1 Constructivity . . . . . . . . . . . . . . . . . . . . 92
8.4.2 Constraint. . . . . . . . . . . . . . . . . . . . . . . 92
8.4.3 Evolution . . . . . . . . . . . . . . . . . . . . . . . 93
8.4.4 Analysis . . . . . . . . . . . . . . . . . . . . . . . . 94
8.5 Means of Mechanization . . . . . . . . . . . . . . . . . . . 94
8.5.1 SAT Solvers . . . . . . . . . . . . . . . . . . . . . . 94
8.5.2 Abductive Logic Programming . . . . . . . . . . . 96
8.5.3 Answer Set Programming . . . . . . . . . . . . . . 96
8.5.4 Future Demands . . . . . . . . . . . . . . . . . . . 97
8.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 98
9 Computational Caricature 101
9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 102
9.2 Computational Caricatures . . . . . . . . . . . . . . . . . 103
9.2.1 Visual Caricature . . . . . . . . . . . . . . . . . . . 103
9.2.2 Procedural Portraits and Computational Caricature 104
9.3 Computational Caricature of the Game Design Process . . 106
9.4 Exemplars . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
9.4.1 A Designer in a Box . . . . . . . . . . . . . . . . . 108
9.4.2 Cooperating with the Machine . . . . . . . . . . . 109
9.4.3 Imagining Gameplay . . . . . . . . . . . . . . . . . 110
9.4.4 Summary . . . . . . . . . . . . . . . . . . . . . . . 112
9.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 112
10 ASP for Design Automation 115
10.1 ASP in Context . . . . . . . . . . . . . . . . . . . . . . . . 116
10.1.1 AnsProlog as a Little Language . . . . . . . . . . . 116
10.1.2 Perspectives . . . . . . . . . . . . . . . . . . . . . . 119
CONTENTS vii
10.2 Design Spaces in ASP . . . . . . . . . . . . . . . . . . . . 120
10.2.1 Representing Artifacts . . . . . . . . . . . . . . . . 122
10.2.2 Representing Spaces . . . . . . . . . . . . . . . . . 123
10.2.3 Modeled and Unmodeled Properties . . . . . . . . 123
10.2.4 Modeling, Solving, Interpretation, and Refinement 124
10.3 Programming Tutorials . . . . . . . . . . . . . . . . . . . 129
10.3.1 Hello Soggy World . . . . . . . . . . . . . . . . . . 129
10.3.2 Graph Coloring, Complexity, and Visualization . . 131
10.3.3 GolombRulers, Optimization, andNumericalCon-
straints . . . . . . . . . . . . . . . . . . . . . . . . 136
10.4 Existing Design Automation Examples . . . . . . . . . . . 140
10.4.1 Diorama . . . . . . . . . . . . . . . . . . . . . . . 140
10.4.2 Anton . . . . . . . . . . . . . . . . . . . . . . . . 144
10.4.3 Toast. . . . . . . . . . . . . . . . . . . . . . . . . 147
10.5 Modeling Tutorials . . . . . . . . . . . . . . . . . . . . . . 149
10.5.1 Chess Mazes . . . . . . . . . . . . . . . . . . . . . 149
10.5.2 Strategy Game Maps. . . . . . . . . . . . . . . . . 157
10.5.3 PlatformerLevelswithSupportforMixed-Initiative
Interaction . . . . . . . . . . . . . . . . . . . . . . 163
11 Applied Systems Overview 173
12 Ludocore 175
12.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
12.2 Building Games on the Event Calculus . . . . . . . . . . . 176
12.3 The Logical Game Engine . . . . . . . . . . . . . . . . . . 178
12.3.1 State, Events, and Consequences . . . . . . . . . . 180
12.3.2 Player Model Interface . . . . . . . . . . . . . . . . 182
12.3.3 Relation to the General Event Calculus . . . . . . 183
12.4 Ludocore in Action . . . . . . . . . . . . . . . . . . . . . 184
12.4.1 Gameplay Trace Inference . . . . . . . . . . . . . . 184
12.4.2 Modifying Rules and Configuration . . . . . . . . . 186
12.4.3 Using Player and Nature Models . . . . . . . . . . 188
12.5 Applications Enabled. . . . . . . . . . . . . . . . . . . . . 188
12.5.1 Game Design . . . . . . . . . . . . . . . . . . . . . 188
12.5.2 Crafting Game Playing Agents . . . . . . . . . . . 190
12.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 190
13 Biped 191
13.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
13.2 Playtesting Background . . . . . . . . . . . . . . . . . . . 193
13.2.1 Playtesting with Humans . . . . . . . . . . . . . . 193
13.2.2 Playtesting with Machines . . . . . . . . . . . . . . 193
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13.3 System Overview . . . . . . . . . . . . . . . . . . . . . . . 194
13.3.1 Game Sketching Language . . . . . . . . . . . . . . 194
13.3.2 Interface elements . . . . . . . . . . . . . . . . . . 196
13.3.3 Supporting Playtesting. . . . . . . . . . . . . . . . 198
13.3.4 Implementation . . . . . . . . . . . . . . . . . . . . 200
13.4 Example Prototype . . . . . . . . . . . . . . . . . . . . . . 201
13.4.1 Game Mechanics . . . . . . . . . . . . . . . . . . . 201
13.4.2 UI Bindings . . . . . . . . . . . . . . . . . . . . . . 201
13.4.3 Human Playtesting . . . . . . . . . . . . . . . . . . 203
13.4.4 Machine Playtesting . . . . . . . . . . . . . . . . . 203
13.5 Conclusions and Future Work . . . . . . . . . . . . . . . . 204
14 Variations Forever 207
14.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
14.1.1 Variations Forever as a Game Project . . . . . . . 209
14.1.2 Variations Forever as a Research Project . . . . . 209
14.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . 211
14.3 Representing Game Rulesets in Logical Terms . . . . . . . 213
14.4 VF’s Generative Space . . . . . . . . . . . . . . . . . . . . 214
14.5 Zooming in on Games of Interest . . . . . . . . . . . . . . 217
14.6 Generating Playable Mini-games . . . . . . . . . . . . . . 218
14.6.1 Game Generator . . . . . . . . . . . . . . . . . . . 218
14.6.2 Game Engine . . . . . . . . . . . . . . . . . . . . . 219
14.7 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
14.7.1 Coupling between Generator and Engine . . . . . . 220
14.7.2 Tradeoffs in Levels of Abstraction . . . . . . . . . 220
14.7.3 Evaluation . . . . . . . . . . . . . . . . . . . . . . 221
14.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 222
15 Refraction Tools 223
15.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 224
15.2 Related Work . . . . . . . . . . . . . . . . . . . . . . . . . 226
15.3 Answer Set Programming . . . . . . . . . . . . . . . . . . 227
15.3.1 ASP for PCG . . . . . . . . . . . . . . . . . . . . . 227
15.4 Refraction Puzzle Design . . . . . . . . . . . . . . . . . . 228
15.5 Problem Formalization . . . . . . . . . . . . . . . . . . . . 230
15.5.1 Mission Generation . . . . . . . . . . . . . . . . . . 231
15.5.2 Grid Embedding . . . . . . . . . . . . . . . . . . . 231
15.5.3 Puzzle Solving . . . . . . . . . . . . . . . . . . . . 232
15.6 System Descriptions . . . . . . . . . . . . . . . . . . . . . 234
15.6.1 Feed-Forward Mission Generation. . . . . . . . . . 234
15.6.2 Grid Embedding with DFS . . . . . . . . . . . . . 235
15.6.3 Puzzle Solving with DFS . . . . . . . . . . . . . . 236
CONTENTS ix
15.6.4 Grid Embedding with ASP . . . . . . . . . . . . . 237
15.6.5 Mission Generation with ASP . . . . . . . . . . . . 238
15.6.6 Puzzle Solving with ASP . . . . . . . . . . . . . . 239
15.7 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
15.7.1 Quantitative Comparisons . . . . . . . . . . . . . . 240
15.7.2 Qualitative Comparisons. . . . . . . . . . . . . . . 241
15.8 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 242
16 Rational Curiosity 245
16.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 245
16.2 Game Design Practices . . . . . . . . . . . . . . . . . . . . 247
16.3 An Analogy with Science . . . . . . . . . . . . . . . . . . 248
16.3.1 Scientific Practices . . . . . . . . . . . . . . . . . . 248
16.3.2 Automated Discovery . . . . . . . . . . . . . . . . 249
16.4 Newell’s Knowledge Level . . . . . . . . . . . . . . . . . . 250
16.5 Creativity as Rational Curiosity. . . . . . . . . . . . . . . 252
16.5.1 Transformational Creativity in Game Design . . . 253
16.6 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 256
16.6.1 Computational Creativity in Game Design. . . . . 256
16.6.2 New Perspective for Computational Creativity . . 258
16.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 260
17 Evaluation 261
17.1 ASP for PCG . . . . . . . . . . . . . . . . . . . . . . . . . 263
17.2 Applied Systems . . . . . . . . . . . . . . . . . . . . . . . 265
17.2.1 Ludocore . . . . . . . . . . . . . . . . . . . . . . . 265
17.2.2 Biped . . . . . . . . . . . . . . . . . . . . . . . . . 266
17.2.3 Variations Forever . . . . . . . . . . . . . . . . . . 271
17.2.4 Refraction Tools . . . . . . . . . . . . . . . . . . . 273
17.3 Recap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276
18 Conclusion 279
18.1 Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 280
18.1.1 Amplify creativity of human game designers . . . . 280
18.1.2 Support deep, play-time design automation . . . . 280
18.1.3 Demonstrate tools that respect design problems. . 281
18.2 Research Context . . . . . . . . . . . . . . . . . . . . . . . 281
18.2.1 Game Design . . . . . . . . . . . . . . . . . . . . . 281
18.2.2 Design Studies . . . . . . . . . . . . . . . . . . . . 282
18.2.3 Computational Creativity . . . . . . . . . . . . . . 282
18.2.4 Symbolic AI. . . . . . . . . . . . . . . . . . . . . . 283
18.3 Contributions . . . . . . . . . . . . . . . . . . . . . . . . . 283
18.4 Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . 284
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