Abstract
Artificial intelligence in digital games has developed in the last 40 years. It has a long and deep history with digital games. AI techniques in digital games evolved independently and differently from the academic AI research of science and engineering which require functionality in the real world. Digital games have complex and large-scale virtual 2D/3D worlds where game characters live in, recognize, make decisions, and design their motions to fitting their environment. The digital world of games is larger, more complex, and more detailed than any other virtual world. It is the most suitable experimental field to study and evaluate AI technologies in the virtual world. The AI for a game character is called “Character AI” and its function is for characters to make decisions. This is much different from functional AI in academic research, and making a character means to create one whole intelligence. The other unique AIs are “Navigation AI” which analyzes and recognizes the environment of game world and “Meta AI” which dynamically controls and changes the progress, situation, and drama of the game. These three AIs, namely, Character AI, Navigation AI, and Meta AI, cooperate with each other and develop one unified system to form a dynamic user experience. In addition, recently learning and evolution approaches have been introduced into AI for digital games. In this chapter such current status of AI in digital games is described.
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Recommended Reading
J. Abercrombie, Bringing bioShock infinite’s Elizabeth to life: an AI development postmortem, in GDC 2014 (2014), http://www.gdcvault.com/play/1015387/Animation-Driven-Locomotion-for-Smoother
G. Alt, K. King, Chapter 8.6, A dynamic reputation system based on event knowledge, in AI Game Programming Wisdom, vol. 1, Charles River Media, Boston (2002), pp. 426–435
T. Ando, Soccer game AI system for “Sakatsuku DS”, in CEDEC 2010 (2010), http://cedil.cesa.or.jp/session/detail/379
B. Anguelov, Managing the movement, in GDC 2013 (2013), http://www.gdcvault.com/play/1018145/Managing-the-Movement-Getting-Your
B. Anguelov, G. Leblanc, S. Harris, Animation-driven locomotion for smoother navigation, in GDC 2012 (2012), http://www.gdcvault.com/play/1015387/Animation-Driven-Locomotion-for-Smoother
N.A. Bernstein, Dexterity and Its Development (Psychology Press, New York, 1996)
M. Booth, Replayable cooperative game design: Left 4 Dead, in GDC 2009 (2009a), http://www.valvesoftware.com/company/publications.html
M. Booth, The AI systems of Left 4 Dead, in AIIDE 2009 (2009b), http://www.valvesoftware.com/company/publications.html
D. Braben, Classic game postmortem – ELITE, in GDC 2011 (2011), http://www.gdcvault.com/play/1014807/Classic-Game-Postmortem
D. Brewer, AI postmortems: Assassin’s Creed III, XCOM: Enemy Unknown, and Warframe, in GDC 2013 (2013), http://www.gdcvault.com/play/1018223/AI-Postmortems-Assassin-s-Creed
D. Brewer, The living AI in Warframe’s procedural space ships, in Game AI Conference (2014), http://gameaiconf.com/recording/living-ai-of-warframe/
R. Brooks, A robust layered control system for a mobile robot. IEEE J. Robot. Autom. 2(1), 14–23 (1986)
C. Browne, F. Maire, Evolutionary game design. IEEE Trans. Comput. Intell. AI Games 2(1), 1–16 (2010)
M. Buckland, Evolving neural net topologies, in AI Techniques for Game Programming (Cengage Learning PTR, 2002)
M. Buckland, Chapter 9, Goal-driven agent behavior, in Programming Game AI by Example (Wordware/Jones & Bartlett Learning, Burlington, 2004a)
M. Buckland, Chapter 8, Practical path planning, in Programming Game AI by Example (Wordware/Jones & Bartlett Learning, Burlington, 2004b)
M. Buckland, Chapter 5, The secret life of graphs, in Programming Game AI by Example (Wordware/Jones & Bartlett Learning, Burlington, 2004c)
R. Burke, D. Isla, M. Downie, Y. Ivanov, B. Blumberg, Creature smarts: the art and architecture of a virtual brain, in Proceedings of the Game Developers Conference, San Jose (2001), pp. 147–166
M. Büttner, Reinforcement learning-based character locomotion in Hitman: absolution, in Game AI Conference (2012), http://gameaiconf.com/recording/hitman-reinforcement/
A. Canary, Free-range AI, in GDC 2014 (2014), http://www.gdcvault.com/play/1020110/Free-Range-AI-Creating-Compelling
A. Champandard, On the AI strategy for KILLZONE 2’s multiplayer bots, AiGameDev (2008), http://aigamedev.com/open/coverage/killzone2/
S. Dahlskog, J. Togelius, A multi-level level generator, in Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG), Dortmund (2014)
M. Dawe, Chapter 28, Beyond the Kung-Fu circle, A K Peters/CRC Press, Boca Raton, in Game AI Pro (2013), pp. 369–375
R. Evans, 11.2. Varieties of learning, AI Wisdom, vol. 1 (2002), pp. 567–578
R. Evans, Modeling individual personalities in The Sims 3, in GDC 2010 (2010), http://www.gdcvault.com/play/1012450/Modeling-Individual-Personalities-in-The
K. Fauerby, Crowds in Hitman: absolution, in GDC 2012 (2012), http://www.gdcvault.com/play/1015315/Crowds-in-Hitman
K. Forbus, Simulation and modeling: under the hood of The Sims, Northwestern University, Lecture note (2002), http://www.cs.northwestern.edu/%7Eforbus/c95-gd/lectures/The_Sims_Under_the_Hood_files/frame.htm
J.J. Gibson, The Ecological Approach to Visual Perception (Routledge, Florence, 1986)
S. Grand, D. Cliff, Creatures: entertainment software agents with artificial life. Auton. Agent. Multi-Agent Syst. 1, 39–57 (1997)
F. Gravot, T. Yokoyama, Y. Miyake, Following a path(movie) (2012a), https://www.youtube.com/watch?v=9_vdpndn4jI
F. Gravot, T. Yokoyama, Y. Miyake, Dropping(movie) (2012b), https://www.youtube.com/watch?v=o3ihN2kSzMs
F. Gravot, T. Yokoyama, Y. Miyake, Chapter 20, Precomputed pathfinding for large and detailed worlds on MMO servers, A K Peters/CRC Press, Boca Raton, in Game AI Pro (2013), pp. 269–287
J. Gregory, Game Engine Architecture (A K Peters/CRC Press, Boca Raton, 2009a)
J. Gregory, State-based scripting in uncharted 2: among Thieves, in GDC 2009 (2009b), http://www.gdcvault.com/play/1730/State-Based-Scripting-in-UNCHARTED
J. Griesemer, The illusion of intelligence: the integration of AI and level design in Halo, in GDC 2002 Proceedings Archiv (2002), http://halo.bungie.net/inside/publications.aspx
D. Guay, Procedural data generation in FAR CRY 2, in GDC 2008, San Francisco (2008)
J. Guay, Real-time sound propagation in video games, in GDC 2012 (2012), http://gdcvault.com/play/1015492/Real-time-Sound-Propagation-in
J. Hamaide, Creatures 3 online, in Game AI Conference (2014), http://gameaiconf.com/recording/2014-creatures/
C. Hecker, Spore behavior tree docs (2009), http://chrishecker.com/My_liner_notes_for_spore/Spore_Behavior_Tree_Docs
C. Hecker et al., Real-time motion retargeting to highly varied user-created morphologies. Proc. ACM SIGGRAPH 27(3), 27:1–27:12 (2008)
R. Herbrich, T. Graepel, J. Quiñonero Candela, Halo, Xbox Live the magic of research in microsoft products, Microsoft Research (2008), http://research.microsoft.com/en-us/projects/drivatar/ukstudentday.pptx
V. Hom, J. Marks, Automatic design of balanced board games, in Proceedings of the 3rd Artificial Intelligence and Interactive Digital Entertainment Conference, Stanford (2007), pp. 25–30
R. Ishida, K. Kuwabara, Y. Katagiri, Chapter 4, Blackboard model, in Distributed Artificial Intelligence (Corona Publishing, Tokyo, 1996)
D. Isla, Managing complexity in the Halo2 AI, in Game Developer’s Conference Proceedings 2005 (2005a), http://www.gamasutra.com/view/feature/130663/gdc_2005_proceeding_handling_.php
D. Isla, Dude, where’s my warthog? From pathfinding to general spatial competence, in AIIDE, 2005 (2005b), http://naimadgames.com/publications.html
D. Isla, Halo 3 objective trees: a declarative approach to multi-agent coordination, in Artificial Intelligence and Interactive Digital Entertainment (AIIDE) (2008), http://naimadgames.com/publications.html
D. Isla, B. Blumberg, Chapter 7.1, Blackboard architectures, in AI Game Programming Wisdom, vol. 1, Charles River Media, Boston (2002), pp. 333–344
D. Isla, P. Gorniak, Beyond behavior: an introduction to knowledge representation, in AI Summit, GDC 2009 (2009), http://naimadgames.com/publications.html
D. Isla, R. Burke, M. Downie, B. Blumberg, A layered brain architecture for synthetic creatures, in Proceedings of IJCAI, Seattle (2001)
T. Iwatani, Introduction to Academic Research of PAC-MAN (Enterbrain, Tokyo, 2005a), p. 101
T. Iwatani, Self-game-control-system, in International Game Designers Panel (2005b), http://game.watch.impress.co.jp/docs/20050312/gdc_int.htm
N. Kurachi, Real-Time Motion Retargeting Pipeline in Spore, vol. 125 (CGWORLD, Tokyo, 2009a), pp. 80–85
N. Kurachi, A Perspective of Procedural Technologie, vol. 125(CGWORLD, Tokyo, 2009b), pp. 44–47
M. Leeuw, The PlayStation®3’s SPUs in the real world: a KILLZONE 2 case study, in GDC 2009 (2009), http://www.guerrilla-games.com/publications.html
Microsoft Research: Drivatar™ in Forza Motorsport (2014), http://research.microsoft.com/en-us/projects/drivatar/forza.aspx
MIT Synthetic Character Group (2003), http://characters.media.mit.edu/
Y. Miyake, A perspective of game AI in“Chrome Hounds”, in CEDEC 2006 (2006), http://cedil.cesa.or.jp/session/detail/50
Y. Miyake, Chapter 5, Managing and controlling contents technology, in Research Report of Advanced Technology Application for Digital Contents Creation (Digital Content Association of Japan, Tokyo, 2007a)
Y. Miyake, Chapter 3, Game AI technologies, in Research Report of Advanced Technology Application for Digital Contents Creation (Digital Content Association of Japan, 2007b), http://www.dcaj.or.jp/project/report/pdf/2007/dc08_07.pdf
Y. Miyake, How to use AI technologies to develop digital games. J. Jpn. Soc. Artif. Intell. 23(1), 44–51 (2008a)
Y. Miyake, Game AI technologies and procedural techniques in Spore, in Digital Game Research Association Japan, 14th Monthly Seminar, Chiba (2008b), http://digrajapan.org/?wpdmact=process&did=Ni5ob3RsaW5r
Y. Miyake, Chapter 23, Digital game AI, in Digital Game Textbook (Softbank Publishing, Tokyo, 2010a), pp. 214–218
Y. Miyake, Applied AI and procedural technologies for online game. J. Jpn. Soc. Fuzzy Theory Intell. Inform. 22(6), 745–756 (2010b)
Y. Miyake, Chapter 22, Procedural technology, in Digital Game Textbook (Softbank Publishing, Tokyo, 2010c), pp. 395–420
Y. Miyake, Chapter 5, The progress and important things of digital game AI, in Core Technologies in Japanese Video Games (Softbank Creative, Tokyo, 2011), pp. 127–214
Y. Miyake, Introduction to Game AI, vol. 68 (WEB + DB Press/Gijutsu-Hyohron, Tokyo, 2012a), pp. 87–120
Y. Miyake, Recent research topics summaries for next-generation digital game AI, in Game Programming Workshop 2012 Proceedings, Hakone 2012(6) (2012b), pp. 108–113
Y. Miyake, The fundamental theory of digital game AI. J. Virtual Real. Soc. Jpn. 18(3), 28–33 (2013)
Y. Miyake, AI engine in digital game. J. Inst. Image Inf. Telev. Eng. 68(2), 125–130 (2014)
Y. Miyake, T. Yokoyama, T. Kitazaki, Developing character AI based on agent architecture in digital games, in 4th Digital Content Symposium, Proceedings, 2-2 (2008)
Y. Morikawa, Use of artificial intelligence for video game. J. Jpn. Soc. Artif. Intell. 14(2), 214–218 (1999)
Y. Morikawa, Affinity of game and AI, in CEDEC 2008 (2008), http://cedil.cesa.or.jp/session/detail/156
K. Namiki, The case study of affordance oriented AI in “Monster Hunter Diary: Poka Poka Airou Village”, in CEDEC 2011 (2011), http://cedil.cesa.or.jp/session/detail/697
D. Nau et al., SHOP2: an HTN planning system. J. Artif. Intell. Res. 20, 379–404 (2013), http://www.guerrilla-games.com/publications.html
M. Nelson, Encoding and generating videogame mechanics, in Computational Intelligence and Games 2012 Tutorial (2012), http://www.kmjn.org/notes/generating_mechanics_bibliography.html
M. Nelson, M. Mateas, Towards automated game design, in AI*IA 2007: Artificial Intelligence and Human-Oriented Computing, Lecture Notes in Computer Science, Springer, Berlin 4733 (2007), pp. 626–637
Neuro-evolving robotic operatives (2005), http://nerogame.org
N. Okamura, Hierarchical goal oriented planning and machine control in ARMORED CORE V, in CEDEC 2011 (2011a), http://cedil.cesa.or.jp/session/detail/591
N. Okamura, Pathfinding in ARMORED CORE V, in CEDEC 2011 (2011b), http://cedil.cesa.or.jp/session/detail/593
J. Orkin, Chapter 3.4, Applying goal-oriented planning for games, in AI Game Programming Wisdom, vol. 2, Charles River Media, Boston (2003), pp. 217–227
J. Orkin, Agent architecture considerations for real-time planning in games, in AIIDE 2005 (2005), http://web.media.mit.edu/~jorkin/
J. Orkin, 3 states & a plan: the AI of F.E.A.R., in Game Developer’s Conference Proceedings (2006), http://web.media.mit.edu/~jorkin/
B. Pell, METAGAME in symmetric chess-like games, in Heuristic Programming in Artificial Intelligence 3 – The Third Computer Olympiad (Ellis Horwood, Hemel Hemstead, 1992)
H. Penny Nii, The blackboard model of problem solving and the evolution of blackboard architectures. AI Mag. 7(2), 38–53 (1986a), http://www.aaai.org/ojs/index.php/aimagazine/article/view/537
H. Penny Nii, Blackboard application systems, blackboard systems and a knowledge engineering perspective. AI Mag. 7(3), 82–107 (1986b), http://www.aaai.org/ojs/index.php/aimagazine/article/view/550
R. Pillosu, Coordinating agents with behavior trees, in Paris Game Conference (2009), http://aigamedev.com/open/coverage/paris09-report/#session3
D. Pottinger, Terrain analysis for realtime strategy games, in GDC 2000, San Jose (2000)
S. Rabin, Agent awareness and knowledge representation, in Game AI Pro (CRC Press, Boca Raton, 2013)
M. Robbins, Chapter 30, Using neural networks to control agent threat response, A K Peters/CRC Press, Boca Raton, in Game AI Pro (2013), pp. 391–399
S. Russell, P. Norvig, Artificial Intelligence, A Modern Approach, 3rd edn. (Prentice Hall, Upper Saddle River, 2009)
N. Shaker, G. Yannakakis, J. Togelius, Digging deeper into platform game level design, in Proceedings of the European Conference on Applications of Evolutionary Computation (EvoGames), Malaga (2012)
M. Shaker, M. Sarhan, O. Naameh, N. Shaker, J. Togelius, Automatic generation and analysis of physics-based puzzle games, in Proceedings of the IEEE Conference on Computational Intelligence and Games, Niagara Falls (2013)
G. Snook, Chapter 3.6, Simplified 3D movement and pathfinding using navigation meshes, in Game Programming Gems, vol. 1 (Charles River Media, Boston, 2000), pp. 288–304
K. Stanley, B. Bryant, R. Miikkulainen, Evolving neural network agents in the NERO video game, in Proceedings of the IEEE 2005 Symposium on Computational Intelligence and Games, Colchester (2005)
R. Straatman, A. Beij, W.V.D. Sterren, Killzone’s AI: Dynamic Procedural Combat Tactics (2005), http://www.cgf-ai.com/docs/straatman_remco_killzone_ai.pdf
R. Straatman, T. Verweij, A. Champandard, Killzone 2 multiplayer bots, in Paris Game/AI Conference (2009), http://www.guerrilla-games.com/publications.html
R. Straatman, T. Verweij, A. Champandard, R. Morcus, H. Kleve, Chapter 29, Hierarchical AI for multiplayer bots in Killzone 3, A K Peters/CRC Press, Boca Raton, in Game AI Pro (2013), pp. 377–390
M. Tanabe, Engineering and design of soccer AI in WCCF, in Digital Game Research Association of Japan, Regular Open Seminar of May in 2009 (2009), http://digrajapan.org/?wpdmact=process&did=OS5ob3RsaW5r
J. Togelius, J. Schmidhuber, An experiment in automatic game design, in Proceedings of the 2008 IEEE. Conference on Computational Intelligence and Games, Perth (2008), pp. 111–118
UNIX free software developed by Michael Toy, Glenn Wichman, Ken Arnold (1980)
W. van der Sterren, Chapter 13, Hierarchical plan-space planning for multi-unit combat maneuvers, in Game AI Pro, vol. 1, A K Peters/CRC Press, Boca Raton (2013), pp. 169–183
J. von Uexküll, Streifzüge durch die Umwelten von Tieren und Menschen: Ein Bilderbuch unsichtbarer Welten (Rowohlt, Reinbek, 1956)
M. Walsh, Dynamic navmesh – AI in the dynamic environment of splinter cell: conviction, in GDC 2010 (2010), http://www.gdcvault.com/play/1012651/Dynamic-Navmesh-AI-in-the
M. Walsh, Modeling AI perception and awareness in splinter cell: blacklist, in GDC 2014 (2014), http://www.gdcvault.com/play/1020195/Modeling-AI-Perception-and-Awareness
M. Widmark, Terrain in Battlefield 3: modern, complete and scalable system, in GDC 2012 (2012), http://www.gdcvault.com/play/1015414/Terrain-in-Battlefield-3-A
S. Yoneda, [SQEXOC 2012]AI technologies in FFXIV, 4gamers (2012), http://www.4gamer.net/games/032/G003263/20121205079/
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Miyake, Y. (2017). Current Status of Applying Artificial Intelligence in Digital Games. In: Nakatsu, R., Rauterberg, M., Ciancarini, P. (eds) Handbook of Digital Games and Entertainment Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-4560-50-4_70
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