Game AI revisited
Open accessAbstract
More than a decade after the early research efforts on the use of artificial intelligence (AI) in computer games and the establishment of a new AI domain the term ``game AI'' needs to be redefined. Traditionally, the tasks associated with game AI revolved around non player character (NPC) behavior at different levels of control, varying from navigation and pathfinding to decision making. Commercial-standard games developed over the last 15 years and current game productions, however, suggest that the traditional challenges of game AI have been well addressed via the use of sophisticated AI approaches, not necessarily following or inspired by advances in academic practices. The marginal penetration of traditional academic game AI methods in industrial productions has been mainly due to the lack of constructive communication between academia and industry in the early days of academic game AI, and the inability of academic game AI to propose methods that would significantly advance existing development processes or provide scalable solutions to real world problems. Recently, however, there has been a shift of research focus as the current plethora of AI uses in games is breaking the non-player character AI tradition. A number of those alternative AI uses have already shown a significant potential for the design of better games.
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Cites
Motivations for Play in Online Games
Yee, N. (2006) · CyberPsychology & Behavior · doi:10.1089/cpb.2006.9.772 · Cited by 2,939 · see citing works
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797 · see citing works
A casual revolution: reinventing video games and their players
(2010) · Choice Reviews Online · doi:10.5860/choice.47-6689 · Cited by 885 · see citing works
Search-Based Procedural Content Generation: A Taxonomy and Survey
Togelius, J., Yannakakis, G. N., Stanley, K. O., & Browne, C. (2011) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2011.2148116 · Cited by 706 · see citing works
Self-citationExperience-Driven Procedural Content Generation
Yannakakis, G. N., & Togelius, J. (2011) · IEEE Transactions on Affective Computing · doi:10.1109/t-affc.2011.6 · Cited by 536 · see citing works
Self-citationProbabilistic assessment of user's emotions in educational games
Conati, C. (2002) · Applied Artificial Intelligence · doi:10.1080/08839510290030390 · Cited by 498 · see citing works
Human-Level AI's Killer Application: Interactive Computer Games
Laird, J. E., & van Lent, M. (2000) · National Conference on Artificial Intelligence · Cited by 416 · see citing works
Facade: An Experiment in Building a Fully-Realized Interactive Drama
Mateas, M., & Stern, A. (2003) · Cited by 409 · see citing works
Rabin, S. (2003) · Cited by 406 · see citing works
In-game: from immersion to incorporation
(2012) · Choice Reviews Online · doi:10.5860/choice.49-2483 · Cited by 391 · see citing works
Player modeling using self-organization in Tomb Raider: Underworld
Drachen, A., Canossa, A., & Yannakakis, G. N. (2009) · IEEE Symposium on Computational Intelligence and Games (CIG) · doi:10.1109/cig.2009.5286500 · Cited by 288 · see citing works
Self-citationTowards automatic personalised content creation for racing games
Togelius, J., Nardi, R. D., & Lucas, S. M. (2007) · IEEE Symposium on Computational Intelligence and Games (CIG) · doi:10.1109/cig.2007.368106 · Cited by 283 · see citing works
F�rnkranz, J., & Hllermeier, E. (2010) · Cited by 259 · see citing works
Kessous, L., Castellano, G., & Caridakis, G. (2010) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-009-0025-5 · Cited by 256 · see citing works
Modeling Player Experience for Content Creation
Pedersen, C. R., Togelius, J., & Yannakakis, G. N. (2010) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2010.2043950 · Cited by 233 · see citing works
Self-citationTowards Automatic Personalized Content Generation for Platform Games
Shaker, N., Yannakakis, G. N., & Togelius, J. (2010) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v6i1.12399 · Cited by 228 · see citing works
Self-citationA data mining approach to strategy prediction
Weber, B. G., & Mateas, M. (2009) · IEEE Symposium on Computational Intelligence and Games (CIG) · doi:10.1109/cig.2009.5286483 · Cited by 226 · see citing works
Real-Time Game Adaptation for Optimizing Player Satisfaction
Yannakakis, G. N., & Hallam, J. C. T. (2009) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2009.2024533 · Cited by 198 · see citing works
Self-citationAutomatic Content Generation in the Galactic Arms Race Video Game
Hastings, E. J., Guha, R. K., & Stanley, K. O. (2009) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2009.2038365 · Cited by 178 · see citing works
Modeling player experience in Super Mario Bros
Pedersen, C., Togelius, J., & Yannakakis, G. N. (2009) · IEEE Symposium on Computational Intelligence and Games (CIG) · doi:10.1109/cig.2009.5286482 · Cited by 168 · see citing works
Self-citationA Turing Test for Computer Game Bots
Hingston, P. (2009) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2009.2032534 · Cited by 167 · see citing works
Tanagra: Reactive Planning and Constraint Solving for Mixed-Initiative Level Design
Smith, G., Whitehead, J., & Mateas, M. (2011) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2011.2159716 · Cited by 156 · see citing works
Evolving content in the Galactic Arms Race video game
Hastings, E. J., Guha, R. K., & Stanley, K. O. (2009) · IEEE Symposium on Computational Intelligence and Games (CIG) · doi:10.1109/cig.2009.5286468 · Cited by 144 · see citing works
TOWARDS OPTIMIZING ENTERTAINMENT IN COMPUTER GAMES
Yannakakis, G. N., & Hallam, J. C. T. (2007) · Applied Artificial Intelligence · doi:10.1080/08839510701527580 · Cited by 121 · see citing works
Self-citationTowards affective camera control in games
Yannakakis, G. N., Martínez, H. P., & Jhala, A. H. (2010) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-010-9078-0 · Cited by 112 · see citing works
Self-citationEvolving Opponents for Interesting Interactive Computer Games
Yannakakis, G. N., & Hallam, J. C. T. (2004) · The MIT Press eBooks · doi:10.7551/mitpress/3122.003.0062 · Cited by 110 · see citing works
Self-citationMultiobjective exploration of the StarCraft map space
Togelius, J., Preuß, M., Beume, N., et al. (2010) · IEEE Conference on Computational Intelligence and Games (CIG) · doi:10.1109/itw.2010.5593346 · Cited by 108 · see citing works
Emotion-Oriented Systems: The Humaine Handbook
Petta, P., Pélachaud, C., & Cowie, R. (2011) · Cognitive technologies · doi:10.1007/978-3-642-15184-2 · Cited by 101 · see citing works
A Metric for Entertainment of Boardgames: Its Implication for Evolution of Chess Variants
Iida, H., Takeshita, N., & Yoshimura, J. (2003) · IFIP advances in information and communication technology · doi:10.1007/978-0-387-35660-0_8 · Cited by 100 · see citing works
Research in human-level AI using computer games
Laird, J. E. (2002) · Communications of the ACM · doi:10.1145/502269.502290 · Cited by 100 · see citing works
Automatic generation and evaluation of recombination games
Browne, C. (2008) · Cited by 92 · see citing works
Ranking vs. Preference: A Comparative Study of Self-reporting
Yannakakis, G. N., & Hallam, J. (2011) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-24600-5_47 · Cited by 90 · see citing works
Self-citationModeling enjoyment preference from physiological responses in a car racing game
Tognetti, S., Garbarino, M., Bonarini, A., & Matteucci, M. (2010) · IEEE Conference on Computational Intelligence and Games (CIG) · doi:10.1109/itw.2010.5593337 · Cited by 75 · see citing works
Real-time challenge balance in an RTS game using rtNEAT
Olesen, J. K., Yannakakis, G. N., & Hallam, J. C. T. (2008) · IEEE Symposium on Computational Intelligence and Games (CIG) · doi:10.1109/cig.2008.5035625 · Cited by 75 · see citing works
Self-citationAdapting Models of Visual Aesthetics for Personalized Content Creation
Liapis, A., Yannakakis, G. N., & Togelius, J. (2012) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2012.2192438 · Cited by 70 · see citing works
Self-citationPreference Learning for Cognitive Modeling: A Case Study on Entertainment Preferences
Yannakakis, G. N., Μaragoudakis, M., & Hallam, J. C. T. (2009) · IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans · doi:10.1109/tsmca.2009.2028152 · Cited by 70 · see citing works
Self-citationLearning Human-Like Opponent Behavior for Interactive Computer Games
Bauckhage, C., Thurau, C., & Sagerer, G. (2003) · Lecture notes in computer science · doi:10.1007/978-3-540-45243-0_20 · Cited by 63 · see citing works
Player Modeling Impact on Player’s Entertainment in Computer Games
Yannakakis, G. N., & Μaragoudakis, M. (2005) · Lecture notes in computer science · doi:10.1007/11527886_11 · Cited by 60 · see citing works
Self-citationTowards Capturing and Enhancing Entertainment in Computer Games
Yannakakis, G. N., & Hallam, J. C. T. (2006) · Lecture notes in computer science · doi:10.1007/11752912_43 · Cited by 58 · see citing works
Self-citationQueensland University of Technology
(2018) · Palgrave Macmillan UK eBooks · doi:10.1007/978-1-349-94186-5_948 · Cited by 58 · see citing works
Convex Non-negative Matrix Factorization in the Wild
Thurau, C., Kersting, K., & Bauckhage, C. (2009) · Proceedings · doi:10.1109/icdm.2009.55 · Cited by 57 · see citing works
Expressive AI: Games and Artificial Intelligence
Mateas, M. (2003) · DiGRA Digital Library · doi:10.26503/dl.v2003i1.99 · Cited by 49 · cited 1× · see citing works
“…game conference at Harvard [33] and 12 years after Laird’s and van Lent’s seminal article [26] that, in part, established the foundations of game artificial intelligence (AI) and inspired early work in the field [34, 22, 25, 14, 3, 30, 58] the game AI term needs to be revisited and restructured.”
Preference learning for affective modeling
Yannakakis, G. N. (2009) · International Conference on Affective Computing and Intelligent Interaction and workshops · doi:10.1109/acii.2009.5349491 · Cited by 46 · see citing works
Self-citationReview: Intelligent Agents for Computer Games
Nareyek, A. (2000) · Computers and Games · doi:10.1007/3-540-45579-5_28 · Cited by 43 · see citing works
McCoy, J., Treanor, M., Samuel, B., et al. (2012) · International Conference on the Foundations of Digital Games (FDG) · doi:10.1145/2282338.2282384 · Cited by 42 · see citing works
Game Metrics Without Players: Strategies for Understanding Game Artifacts
Nelson, M. (2011) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v7i3.12479 · Cited by 41 · see citing works
Game AI is Dead. Long Live Game AI!
Nareyek, A. (2007) · IEEE Intelligent Systems · doi:10.1109/mis.2007.10 · Cited by 39 · see citing works
Champandard, A. J. (2003) · Cited by 39 · see citing works
New Challenges for Character-Based AI for Games
Blumberg, B. M. (2002) · Cited by 37 · see citing works
2011 IEEE conference on computational intelligence and games
(2011) · IEEE Transactions on Computational Intelligence and AI in Games · doi:10.1109/tciaig.2011.2128770 · Cited by 32 · see citing works
Evolving 3D Buildings for the Prototype Video Game Subversion
Martin, A., Lim, A. E. B., Colton, S., et al. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12239-2_12 · Cited by 22 · see citing works
Difficulty Scaling through Incongruity
van Lankveld, G., Spronck, P. H. M., & Rauterberg, M. (2008) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v4i1.18706 · Cited by 20 · see citing works
Towards more human-like computer opponents
Freed, M. C., Bear, T., Goldman, H., et al. (2000) · Cited by 16 · see citing works
A Neuro-fuzzy Approach to User Attention Recognition
Asteriadis, S., Karpouzis, K., & Kollias, S. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-87536-9_95 · Cited by 15 · see citing works
Optimizing Visual Properties of Game Content Through Neuroevolution
Liapis, A., Yannakakis, G. N., & Togelius, J. (2011) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v7i1.12444 · Cited by 14 · see citing works
Self-citationBidarra, R., de Kraker, K. J., Smelik, R. M., et al. (2010) · TNO Repository · Cited by 12 · see citing works
Learning and Evaluating Human-Like NPC Behaviors in Dynamic Games
Chang, Y.-H., Maheswaran, R. T., Levinboim, T., et al. (2011) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v7i1.12439 · Cited by 11 · see citing works
Behavior Compilation for AI in Games
Orkin, J., Smith, T., & Roy, D. K. (2010) · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · doi:10.1609/aiide.v6i1.12406 · Cited by 8 · see citing works
Modelling Global Pattern Formations for Collaborative Learning Environments
Grappiolo, C., Cheong, Y.-G., Khaled, R., et al. (2012) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2012.17 · Cited by 2 · see citing works
Flagged first, then by citations
Research works printed but not linked: 8
- [1]1. M. Ambinder. Biofeedback in Gameplay: How Valve Measures Physiology to Enhance Gaming Experience. In Game Developers Conference, 2011.
- [10]10. D. Charles and M. Black. Dynamic player modelling: A framework for player-centric digital games. In Proceedings of the International Conference on Computer Games: Artificial Intelligence, Design and Education, pages 29-35, 2004.
- [13]13. A. Drachen, C. Thurau, J. Togelius, and G. N. Yannakakis. Game Telemetry and Metrics, chapter Large-scale Data Mining in Games. Springer-Verlag, 2012.
- [20]20. R. Houlette. Player Modeling for Adaptive Games. AI Game Programming Wisdom II, pages 557-566.
- [45]45. B. Sunshine-Hill, M. Robbins, and C. Jurney. Off the Beaten Path: Non-Traditional Uses of AI. In Game Developers Conference, AI Summit, 2012.
- [49]49. J. Togelius, G. Yannakakis, S. Karakovskiy, and N. Shaker. Believability in Computer Games, chapter Assessing Believability. Springer-Verlag, 2012.
- [54]54. B. Weber and M. Mateas. A Data Mining Approach to Strategy Prediction. In Proceedings of the IEEE Symposium on Computational Intelligence in Games, pages 140-147, Milan, Italy, September 2009. IEEE.
- [68]68. R. Zubek and M. Lewis. Managing the Masses: Crafting AI for Online Games. In Game Developers Conference, AI Summit, 2012.
Cited by
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Generative Agents: Interactive Simulacra of Human Behavior
Park, J. S., O'Brien, J., Cai, C. J., Morris, M. R., Liang, P., & Bernstein, M. S. (2023) · Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology · doi:10.1145/3586183.3606763 · Cited by 2,187 · see citing works
“However, the space of human behavior is vast and complex [85, 108].”
BackgroundInfluentialPredicting player churn in the wild
Hadiji, F., Sifa, R., Drachen, A., Thurau, C., Kersting, K., & Bauckhage, C. (2014) · 2014 IEEE Conference on Computational Intelligence and Games · doi:10.1109/cig.2014.6932876 · Cited by 154 · see citing works
Artificial intelligence moving serious gaming: Presenting reusable game AI components
Westera, W., Prada, R., Mascarenhas, S., Santos, P. A., Dias, J., Guimarães, M., Georgiadis, K., Nyamsuren, E., Bahreini, K., Yumak, Z., et al. (2020) · Education and Information Technologies · doi:10.1007/s10639-019-09968-2 · Cited by 136 · see citing works
Enhancing memory retrieval in generative agents through LLM-trained cross attention networks
Hong, C., & He, Q. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1591618 · Cited by 7 · see citing works
- Authors
- Yannakakis, G. N.
- Affiliations
- IT University of Copenhagen, Copenhagen, Denmark
- Venue
- Proceedings of the 9th conference on Computing Frontiers
- Publisher
- ACM
- Published
- 2012-05-15
- Pages
- 285-292
- OpenAlex
- W2041224215
- Semantic Scholar
- 2d0b34e31f02455c2d370a84645b295af6d59702
- Cited by
- 179
- References
- 59
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 9 · 2023: 13 · 2022: 8 · 2021: 9 · 2020: 13 · 2019: 18 · 2018: 13 · 2017: 9 · 2016: 19 · 2015: 13 · 2014: 14 · 2013: 21 · 2012: 8
- FWCI
- 13.74
- Type
- conference paper
- Language
- en
- Open access
- green
- www.um.edu.mt
- Locations
- ACM International Conference on Computing Frontiers (CF) (publishedVersion)
- OAR@UM (University of Malta) (submittedVersion, other-oa)
- IT University Of Copenhagen (IT University of Copenhagen) (submittedVersion)
- Funders
- Ministério da Ciência, Tecnologia e Inovação
- FP7 Information and Communication Technologies
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence in Games
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Sociology and Political Science › Digital Games and Media
- Keywords
- game AI, non-player character behavior, path finding, navigation, decision-making, game design
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