Perancangan dan Pembuatan Action Game dengan Artificial Intelligence dan Machine Learning
Abstract
Playing games is a way for someone to relieve their stress. However, based on reality, most people are easily to get bored after playing several rounds of game. To overcome this problem, this thesis will create a game where the enemy can give fast respons when fighting the player and may develop the AI’s capabilities.
The genre of this game is action. The AI in this game will use two methods: fuzzy state machine and machine learning. Fuzzy state machine is a method to choose the best response towards the enemy. Machine learning is used to update the active file rules of the enemy.
The result from this experiment stated that action game with fuzzy state machine and machine learning can make the enemy to give better respons after being played by the player.References
[1] Bede, B. 2013. Mathematics of Fuzzy Sets and Fuzzy Logic. Heidelberg: Springer.
[2] Deterding. S, Dixon. D, Khaled. R, dan Nacke. L.E. 2011. Gamification: Toward to Definition. CHI 2011, pp. 1-4.
[3] Epper, R.M., Derryberry, A., dan Jackson, S. 2012. Game-Based Learning: Developing an Institutional Strategy. Retrieved August 9, 2012, Louiseville, CO: EDUCAUSE Center for Applied Research Web Site: http://www.educause.edu/ecar.
[4] Hullermeier, E. 2011. Fuzzy Logic in Machine Learning.
[5] Lilly, J. H. 2010. Fuzzy Control and Identification. Hoboken: John Wiley & Sons, Inc.
[6] Millington, I. 2006. Artificial Intelligence for Games. San Fransico: Elsevier.
[7] Pirovano, M. 2012. The use of Fuzzy Logic for Artificial Intelligence in Games. pp. 1-8.
[8] Porter, N. 2012. Component-Based Game Object System.
[9] Purba, K. R., Hasanah, R. N., & Muslim, M. A. 2013. Implementasi Logika Fuzzy Untuk Mengatur Perilaku Musuh dalam Game Bertipe Action-RPG. Jurnal EECCIS, Vol. 7 (No. 1), pp. 15-20.
[10] Ross, T. J. 2004. Fuzzy Logic with Engineering Applications (2th ed.). Chichester: John Wiley & Sons Ltd.
