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Accuracy Analysis of Decision Making Capability of Artificial Intelligence (AI) Based Digital Game Developed in UNITY 3D Simulator

Year 2022, Volume: 6 Issue: 2, 169 - 176, 30.12.2022

Abstract

Artificial Intelligence (AI) is a universal field for developing artificial methods that mimic human thinking. Computer games are electronic games consisting of hardware and software that involve human interaction with a user interface to generate visual feedback. Nowadays, it is seen that AI technology is increasingly used in computer games to simulate human-like intelligence and create intelligent behaviors. Especially in newly developed computer games, it is seen that AI is integrated into digital games as “Game Artificial Intelligence”. Behind this situation, there is essentially the simulation of game setup and opponent player behavior in digital games by providing decision making, perception and prediction skills with AI. In this research, it is aimed to develop an AI-based computer game (AI-DIGPOKGAME) and accuracy analysis in C# programming language with the open source Unity 3D Game simulator and "Jetbrains Rider" compiler, which allows users to develop their own digital game models. Within the scope of the study, 13 (thirteen) experiments were carried out. In the aforementioned experiments, it has been verified that within the framework of the game setup where the player fights against AI, AI successfully fulfills the basic principles of the game in order to increase competition and keep the fight at the highest level. It is considered that this research will contribute to the field of AI study in terms of revealing the simulation of rival player behavior in games by AI by providing decision making, perception and prediction skills with AI in digital games and developing new computer game models based on AI in the future.

References

  • [1] Suits, B. (1967). What is a Game?. Philosophy of science, 34(2), 148-156.
  • [2] A. Haaranen, T. Rissanen, T. Laatikainen, and J. Kauhanen, “Digital and video games in health promotion: Systematic review of games and health behavior,” Finnish Journal of eHealth and eWelfare, vol. 6, no. 4, pp. 153–163, 2014.
  • [3] M. Palaus, E. M. Marron, R. Viejo-Sobera, and D. Redolar-Ripoll, pp. 248–248, 2017. Neural basis of video gaming: A systematic review. Frontiers in human neuroscience, 248.
  • [4] B. Bostan, B. Tinli, and G. Çatak, pp. 273–295, 2020. [Online]. Available: https://doi.org/10.18691/kulturveiletisim.709869
  • [5] DeDonno, M. A., & Detterman, D. K. (2008). Poker is a skill. Gaming Law Review, 12(1), 31-36.
  • [6] History of poker – My Poker Coaching. Erişim Linki: https://www.mypokercoaching.com/history-of-poker/ Erişim Tarihi: 27.05.2022
  • [7] Adams, H. (2011). History of the United States of America (1801-1817): Volume 4: During the Second Administration of Thomas Jefferson 2 (Vol. 2). Cambridge University Press.
  • [8] KIRCI, P. 3D Game Design with UNITY 3D Game Simulator. International Journal of Multidisciplinary Studies and Innovative Technologies, 3(2), 225-229.
  • [9] Satman, A. G., & YAYIN, K. (2015). UNITY 3D (Vol. 146). KODLAB YAYIN DAĞITIM YAZILIM LTD. ŞTİ.
  • [10] Aydın, H. (2021). Yapay Zekâ Dijital Sistemler ve Uygulamaları (Bölüm 23. Siber Güvenlik ve Yapay Zekâ. Sayfa Nu: 479-509). Editör: Prof. Dr. Cemalettin KUBAT. Aralık 2021, ISBN: 978-605-9594-88-2.
  • [11] Billings, D., Davidson, A., Schaeffer, J., & Szafron, D. (2002). The challenge of poker. Artificial Intelligence, 134(1-2), 201-240.
  • [12] Moravčík, M., Schmid, M., Burch, N., Lisý, V., Morrill, D., Bard, N.& Bowling, M. (2017). Deepstack: Expert-level artificial intelligence in heads-up no-limit poker. Science, 356(6337), 508-513.
  • [13] Brown, N., & Sandholm, T. (2018). Superhuman AI for heads-up no-limit poker: Libratus beats top professionals. Science, 359(6374), 418-424.
  • [14] Pfund, J. (2007). Support Vector Machines in the Machine Learning Classifier for a Texas Hold’em Poker Bot.
  • [15] McNally, P., & Rafii, Z. (2008). Opponent Modeling in Poker Using Machine Learning Techniques. Northwestern University.
  • [16] Costa, A. M. (2019). A Study on Neural Networks for Poker Playing Agents (Doctoral dissertation, PUC-Rio).
  • [17] YİĞİTER, U., & TATAR, E. MİMARLIK VE MEDYA ETKİLEŞİMİNDE OYUN TASARIMI. GSI Journals Serie C: Advancements in Information Sciences and Technologies, 2(1), 1-22.
  • [18] C. E. Shannon, “Programming a Computer for Playing Chess. The London, Edinburgh, and Dublin Philosophical Magazine,” Journal of Science, vol. 41, no. 314, pp. 256–275, 1950.
  • [19] J. X. Chen, “The evolution of computing: AlphaGo,” Computing in Science & Engineering, vol. 18, no. 4, pp. 4–7, 2016.
  • [20] G. N. Yannakakis, 2005. AI in computer games: generating interesting interactive opponents by the use of evolutionary computation.
  • [21] M. Pirovano, The use of fuzzy logic for artificial intelligence in games, Milano, 2012.
  • [22] M. Dehghanı, Z. Montazerı, and O. P. Malık, “DGO: Dice game optimizer,” Gazi University Journal of Science, vol. 32, no. 3, pp. 871– 882, 2019.
  • [23] T. Uzlu and E. S¸ aykol, “Evaluating a Player’s Network Class in a Multiplayer Game with Fuzzy Logic,” Gümüs¸hane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 10, no. 1, pp. 163–173, 2020.
  • [24] A. Lohokare, A. Shah, and M. Zyda, “Deep Learning Bot for League of Legends,” Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, vol. 16, pp. 322–324, 2020.
  • [26] M.Cetin, & Y. Sarıca. Artificial Intelligence Based Game Levelling. Balkan Journal of Electrical and Computer Engineering, 8(2), 147-153.
  • [27] Russell, S., & Norvig, P. (2002). Artificial intelligence: a modern approach.

UNITY 3D Simülatöründe Geliştirilen Yapay Zekâ (YZ) Tabanlı Dijital Oyunun Karar Verme Yeteneğinin Doğruluk Analizi

Year 2022, Volume: 6 Issue: 2, 169 - 176, 30.12.2022

Abstract

Yapay Zekâ (YZ), insanın düşünme yöntemlerini taklit eden yapay yöntemleri geliştirmeye yönelik evrensel bir alandır. Bilgisayar oyunları görsel geri bildirim oluşturmak için bir kullanıcı arayüzü ile insan etkileşimini içeren donanım ve yazılımdan oluşan elektronik oyunlardır. Günümüzde bilgisayar oyunlarında giderek artan oranlarda insan benzeri zekayı simüle etmek ve akıllı davranışlar oluşturmak için YZ teknolojisinin kullanıldığı görülmektedir. Özellikle yeni geliştirilen bilgisayar oyunlarında YZ'nın dijital oyunlara “Oyun Yapay Zekâsı” olarak entegre edildiği görülmektedir. Bu durumun arkasında esasen YZ ile karar verme, algılama ve tahmin becerilerinin sağlanarak dijital oyunlardaki oyun kurgusunun ve rakip oyuncu davranışının simüle edilmesi bulunmaktadır. Bu araştırmada kullanıcıların kendi dijital oyun modellerini geliştirmelerine imkân sağlayan açık kaynak kodlu Unity 3D Oyun simülatörü ve “Jetbrains Rider “derleyicisi ile C# programlama dilinde YZ tabanlı bir bilgisayar oyunun geliştirilmesi (AI-DIGPOKGAME) ve doğruluk analizinin yapılması amaçlanmıştır. Çalışma kapsamında 13 (onüç) adet deney gerçekleştirilmiştir. Söz konusu deneylerde oyuncunun YZ'ya karşı mücadele verdiği oyun kurgusu çerçevesinde YZ'nın rekabeti arttırma ve mücadeleyi daima üst seviyede tutma adına oyunun temel ilkelerini başarıyla gerçekleştirdiği doğrulanmıştır. Bu araştırmanın dijital oyunlarda YZ ile karar verme, algılama ve tahmin becerilerinin sağlanarak oyunlardaki rakip oyuncu davranışının YZ tarafından simüle edilmesinin ortaya konulması ve gelecekte yeni bilgisayar oyun modellerinin YZ tabanlı olarak geliştirilmesi açısından YZ çalışma alanına katkı sağlayacağı değerlendirilmektedir.

References

  • [1] Suits, B. (1967). What is a Game?. Philosophy of science, 34(2), 148-156.
  • [2] A. Haaranen, T. Rissanen, T. Laatikainen, and J. Kauhanen, “Digital and video games in health promotion: Systematic review of games and health behavior,” Finnish Journal of eHealth and eWelfare, vol. 6, no. 4, pp. 153–163, 2014.
  • [3] M. Palaus, E. M. Marron, R. Viejo-Sobera, and D. Redolar-Ripoll, pp. 248–248, 2017. Neural basis of video gaming: A systematic review. Frontiers in human neuroscience, 248.
  • [4] B. Bostan, B. Tinli, and G. Çatak, pp. 273–295, 2020. [Online]. Available: https://doi.org/10.18691/kulturveiletisim.709869
  • [5] DeDonno, M. A., & Detterman, D. K. (2008). Poker is a skill. Gaming Law Review, 12(1), 31-36.
  • [6] History of poker – My Poker Coaching. Erişim Linki: https://www.mypokercoaching.com/history-of-poker/ Erişim Tarihi: 27.05.2022
  • [7] Adams, H. (2011). History of the United States of America (1801-1817): Volume 4: During the Second Administration of Thomas Jefferson 2 (Vol. 2). Cambridge University Press.
  • [8] KIRCI, P. 3D Game Design with UNITY 3D Game Simulator. International Journal of Multidisciplinary Studies and Innovative Technologies, 3(2), 225-229.
  • [9] Satman, A. G., & YAYIN, K. (2015). UNITY 3D (Vol. 146). KODLAB YAYIN DAĞITIM YAZILIM LTD. ŞTİ.
  • [10] Aydın, H. (2021). Yapay Zekâ Dijital Sistemler ve Uygulamaları (Bölüm 23. Siber Güvenlik ve Yapay Zekâ. Sayfa Nu: 479-509). Editör: Prof. Dr. Cemalettin KUBAT. Aralık 2021, ISBN: 978-605-9594-88-2.
  • [11] Billings, D., Davidson, A., Schaeffer, J., & Szafron, D. (2002). The challenge of poker. Artificial Intelligence, 134(1-2), 201-240.
  • [12] Moravčík, M., Schmid, M., Burch, N., Lisý, V., Morrill, D., Bard, N.& Bowling, M. (2017). Deepstack: Expert-level artificial intelligence in heads-up no-limit poker. Science, 356(6337), 508-513.
  • [13] Brown, N., & Sandholm, T. (2018). Superhuman AI for heads-up no-limit poker: Libratus beats top professionals. Science, 359(6374), 418-424.
  • [14] Pfund, J. (2007). Support Vector Machines in the Machine Learning Classifier for a Texas Hold’em Poker Bot.
  • [15] McNally, P., & Rafii, Z. (2008). Opponent Modeling in Poker Using Machine Learning Techniques. Northwestern University.
  • [16] Costa, A. M. (2019). A Study on Neural Networks for Poker Playing Agents (Doctoral dissertation, PUC-Rio).
  • [17] YİĞİTER, U., & TATAR, E. MİMARLIK VE MEDYA ETKİLEŞİMİNDE OYUN TASARIMI. GSI Journals Serie C: Advancements in Information Sciences and Technologies, 2(1), 1-22.
  • [18] C. E. Shannon, “Programming a Computer for Playing Chess. The London, Edinburgh, and Dublin Philosophical Magazine,” Journal of Science, vol. 41, no. 314, pp. 256–275, 1950.
  • [19] J. X. Chen, “The evolution of computing: AlphaGo,” Computing in Science & Engineering, vol. 18, no. 4, pp. 4–7, 2016.
  • [20] G. N. Yannakakis, 2005. AI in computer games: generating interesting interactive opponents by the use of evolutionary computation.
  • [21] M. Pirovano, The use of fuzzy logic for artificial intelligence in games, Milano, 2012.
  • [22] M. Dehghanı, Z. Montazerı, and O. P. Malık, “DGO: Dice game optimizer,” Gazi University Journal of Science, vol. 32, no. 3, pp. 871– 882, 2019.
  • [23] T. Uzlu and E. S¸ aykol, “Evaluating a Player’s Network Class in a Multiplayer Game with Fuzzy Logic,” Gümüs¸hane Üniversitesi Fen Bilimleri Enstitüsü Dergisi, vol. 10, no. 1, pp. 163–173, 2020.
  • [24] A. Lohokare, A. Shah, and M. Zyda, “Deep Learning Bot for League of Legends,” Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, vol. 16, pp. 322–324, 2020.
  • [26] M.Cetin, & Y. Sarıca. Artificial Intelligence Based Game Levelling. Balkan Journal of Electrical and Computer Engineering, 8(2), 147-153.
  • [27] Russell, S., & Norvig, P. (2002). Artificial intelligence: a modern approach.
There are 26 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Mert Sezer Ardal This is me 0000-0002-4702-9172

Hakan Aydın 0000-0002-0122-8512

Yüksel Bal This is me 0000-0003-1816-8162

Publication Date December 30, 2022
Submission Date July 23, 2022
Published in Issue Year 2022 Volume: 6 Issue: 2

Cite

IEEE M. S. Ardal, H. Aydın, and Y. Bal, “UNITY 3D Simülatöründe Geliştirilen Yapay Zekâ (YZ) Tabanlı Dijital Oyunun Karar Verme Yeteneğinin Doğruluk Analizi”, IJMSIT, vol. 6, no. 2, pp. 169–176, 2022.