BibTex RIS Kaynak Göster

GRID-BASED PATHFINDING IN A MOBILE GAME WITH INTELLIGENT AGENTS

Yıl 2018, Cilt: 20 Sayı: 58, 150 - 163, 01.01.2018

Öz

Like in other areas, the use of artificial intelligence (AI) is spreading among computer games, which has become a huge industry. In most of the games, artificial intelligence enables the game characters to move, make decisions about where to move and generate tactical and strategic thinking capability. In this study, a game using artificial intelligence has been developed for mobile device platform. Stimulation of rational movements in game characters was worked on by using an advanced form of AI. To enable this, Simple Reflex Agents method was adopted. With a dynamic programming strategy approach, a goal finding algorithm was used to develop a Goal Based Agents method. It has been observed that movements of the goal based characters became more realistic, owing to their goal focused movements. The evaluation of the test results has shown that the intended result has been accomplished relying on this method

Kaynakça

  • Strong, A.I. 2016. Applications of Artificial Intelligence & Associated Technologies, International Emerging Engineering, Management and Science Jodhpur, India, ss 64-67. of on in Technologies Biomedical,
  • Nilsson, N.J. 2014. Principles of artificial Kaufmann Publishers, 0-934613- 10-9, California, A.B.D. Morgan
  • Johnson, S. 2002. Wild Things, http://www.wired.com/2002 /03/aigames/ (Erişim Tarihi: 20.06.2016).
  • Schölkopf, B. 2015. Artificial intelligence: Learning to see and act, Nature, 518(7540), s. 486-487.
  • Millington, I., Funge, J. 2016. Artificial intelligence for games. CRC Press, 978-0-12-374731-0, Burlington, A.B.D.
  • Alex, J. 2007. Top 10 Most Influential http://aigamedev.com/open/high lights/top-ai-games/ (Erişim Tarihi: 26.06.2016).
  • Stout, B. 1996. Smart moves: Intelligent developer magazine, Gamasutra. Game
  • Russell, S., Norvig, P. 1996. Artificial Intelligence-A Modern Approach, Prentice Hall, of speech
  • Xu, L., Krzyzak, A., Suen, C.Y. 1992. Methods of combining multiple classifiers and their applications recognition, IEEE Transactions on Systems, Man, and Cybernetics, 22(3), s. 418-435.
  • Javidi, B., Horner, J.L. 1994. Optical pattern recognition for validation and security verification, Optical engineering, 33(6), s. 1752-1756.
  • Farooq, S.S., Kim, K.J. 2016. Game player modeling, Encyclopedia of Computer Graphics and Games, Springer International Publishing, s. 1-15.
  • Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., Van Den Driessche, G., Dieleman, S. 2016. Mastering the game of Go with deep neural networks and tree search, Nature, 529(7587), s. 484- 489. [15] Wexler, J. 2002. Artificial Intelligence in Games: A look at the smarts behind Lionhead Studio's "Black and White and where it can go and will go in the future, Doktora Tezi, University of Rochester.
  • Buro, M., Furtak, T. 2004. RTS games and real-time AI research, In Proceedings of the Behavior Representation in Modeling and Simulation Conference (BRIMS), Arlington, Virginia, A.B.D.
  • Graham, R., McCabe, H., Sheridan, S. 2015. Pathfinding in computer games, The ITB Journal, 4(2), 6.
  • Ferguson, D., Likhachev, M., Stentz, A. 2005. A guide to heuristic-based path planning, 15th International Conference Planning & Scheduling, Monterey, California, A.B.D., 510. Automated
  • Anguelov, B. 2011. Video game pathfinding and improvements to discrete search on grid-based maps, Doktora Tezi, University of Pretoria.
  • Hagelback, J. 2015. Hybrid pathfinding in StarCraft, IEEE Transactions on Computational Intelligence and AI in Games, 99, s. 1-10.
  • Reynolds, C.W. 1987. Flocks, herds and behavioral model, ACM SIGGRAPH Computer Graphics, 21(4), s. 25-34.
  • Wang, J.Y., Lin, Y.B. 2012. Game ai: Simulating car racing game by applying pathfinding algorithms, International Journal of Machine Learning and Computing, 2(1), 13.
  • Fayyazi, M., Ghazvini, F.F., Ramzi, A. 2014. Efficient Grid-Based Path Finding Techniques For Android Games Environments, Austrian E- Journals of Universal Scientific Organization, 4(12), s. 1072-1094.

AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA

Yıl 2018, Cilt: 20 Sayı: 58, 150 - 163, 01.01.2018

Öz

Büyük bir endüstri haline gelen oyun alanında, her alanda olduğu gibi yapay zekânın kullanımı yaygınlaşmaktadır. Oyunlar da bulunan yapay zekâ oyuna karakterleri hareket ettirme, nereye hareket etmesi gerektiğine karar verme ve taktiksel veya stratejik düşünme yeteneğini kazandırmak için kullanılmaktadır. Bu çalışmada; mobil platformda yapay zekâ kullanan bir oyun geliştirilmiştir. Geliştirilen yapay zekâ ile oyunda yer alan yapay karakterlere, mantıklı bir şekilde hareket edebilme özelliğinin verilmesi üzerine çalışılmıştır. Bunu sağlayabilmek için ilk olarak basit refleks etmeni yöntemi kullanılmıştır. Dinamik programlama yaklaşımıyla bir yol bulma algoritması kullanılarak hedef tabanlı etmen yöntemi geliştirilmiştir. Geliştirilen yöntemde hedef tabanlı oyuncuların hedefe odaklı hareket etmelerinden dolayı, hareketlerinin daha gerçekçi olduğu tespit edilmiştir. Yapılan test sonuçları değerlendirildiğinde, geliştirilen yöntem ile istenilen sonuca ulaşıldığı görülmüştür

Kaynakça

  • Strong, A.I. 2016. Applications of Artificial Intelligence & Associated Technologies, International Emerging Engineering, Management and Science Jodhpur, India, ss 64-67. of on in Technologies Biomedical,
  • Nilsson, N.J. 2014. Principles of artificial Kaufmann Publishers, 0-934613- 10-9, California, A.B.D. Morgan
  • Johnson, S. 2002. Wild Things, http://www.wired.com/2002 /03/aigames/ (Erişim Tarihi: 20.06.2016).
  • Schölkopf, B. 2015. Artificial intelligence: Learning to see and act, Nature, 518(7540), s. 486-487.
  • Millington, I., Funge, J. 2016. Artificial intelligence for games. CRC Press, 978-0-12-374731-0, Burlington, A.B.D.
  • Alex, J. 2007. Top 10 Most Influential http://aigamedev.com/open/high lights/top-ai-games/ (Erişim Tarihi: 26.06.2016).
  • Stout, B. 1996. Smart moves: Intelligent developer magazine, Gamasutra. Game
  • Russell, S., Norvig, P. 1996. Artificial Intelligence-A Modern Approach, Prentice Hall, of speech
  • Xu, L., Krzyzak, A., Suen, C.Y. 1992. Methods of combining multiple classifiers and their applications recognition, IEEE Transactions on Systems, Man, and Cybernetics, 22(3), s. 418-435.
  • Javidi, B., Horner, J.L. 1994. Optical pattern recognition for validation and security verification, Optical engineering, 33(6), s. 1752-1756.
  • Farooq, S.S., Kim, K.J. 2016. Game player modeling, Encyclopedia of Computer Graphics and Games, Springer International Publishing, s. 1-15.
  • Silver, D., Huang, A., Maddison, C.J., Guez, A., Sifre, L., Van Den Driessche, G., Dieleman, S. 2016. Mastering the game of Go with deep neural networks and tree search, Nature, 529(7587), s. 484- 489. [15] Wexler, J. 2002. Artificial Intelligence in Games: A look at the smarts behind Lionhead Studio's "Black and White and where it can go and will go in the future, Doktora Tezi, University of Rochester.
  • Buro, M., Furtak, T. 2004. RTS games and real-time AI research, In Proceedings of the Behavior Representation in Modeling and Simulation Conference (BRIMS), Arlington, Virginia, A.B.D.
  • Graham, R., McCabe, H., Sheridan, S. 2015. Pathfinding in computer games, The ITB Journal, 4(2), 6.
  • Ferguson, D., Likhachev, M., Stentz, A. 2005. A guide to heuristic-based path planning, 15th International Conference Planning & Scheduling, Monterey, California, A.B.D., 510. Automated
  • Anguelov, B. 2011. Video game pathfinding and improvements to discrete search on grid-based maps, Doktora Tezi, University of Pretoria.
  • Hagelback, J. 2015. Hybrid pathfinding in StarCraft, IEEE Transactions on Computational Intelligence and AI in Games, 99, s. 1-10.
  • Reynolds, C.W. 1987. Flocks, herds and behavioral model, ACM SIGGRAPH Computer Graphics, 21(4), s. 25-34.
  • Wang, J.Y., Lin, Y.B. 2012. Game ai: Simulating car racing game by applying pathfinding algorithms, International Journal of Machine Learning and Computing, 2(1), 13.
  • Fayyazi, M., Ghazvini, F.F., Ramzi, A. 2014. Efficient Grid-Based Path Finding Techniques For Android Games Environments, Austrian E- Journals of Universal Scientific Organization, 4(12), s. 1072-1094.
Toplam 20 adet kaynakça vardır.

Ayrıntılar

Diğer ID JA33GC82NH
Bölüm Araştırma Makalesi
Yazarlar

Semih Utku Bu kişi benim

Kadir Tilki Bu kişi benim

Yayımlanma Tarihi 1 Ocak 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 20 Sayı: 58

Kaynak Göster

APA Utku, S., & Tilki, K. (2018). AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi, 20(58), 150-163.
AMA Utku S, Tilki K. AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA. DEUFMD. Ocak 2018;20(58):150-163.
Chicago Utku, Semih, ve Kadir Tilki. “AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi 20, sy. 58 (Ocak 2018): 150-63.
EndNote Utku S, Tilki K (01 Ocak 2018) AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi 20 58 150–163.
IEEE S. Utku ve K. Tilki, “AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA”, DEUFMD, c. 20, sy. 58, ss. 150–163, 2018.
ISNAD Utku, Semih - Tilki, Kadir. “AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi 20/58 (Ocak 2018), 150-163.
JAMA Utku S, Tilki K. AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA. DEUFMD. 2018;20:150–163.
MLA Utku, Semih ve Kadir Tilki. “AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA”. Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen Ve Mühendislik Dergisi, c. 20, sy. 58, 2018, ss. 150-63.
Vancouver Utku S, Tilki K. AKILLI ETMENLER İLE IZGARA TABANLI BİR MOBİL OYUNDA YOL BULMA. DEUFMD. 2018;20(58):150-63.

Dokuz Eylül Üniversitesi, Mühendislik Fakültesi Dekanlığı Tınaztepe Yerleşkesi, Adatepe Mah. Doğuş Cad. No: 207-I / 35390 Buca-İZMİR.